Distributed antenna systems

ABSTRACT

In a multi-user multiple antenna system, a central processor is communicatively coupled to a plurality of geographically distributed access points via a network. The central processor, the geographically distributed access points, or a plurality of client devices served by the system computes channel estimates of wireless channels between the geographically distributed access points and the client devices. The central processor computes access-point weights from the channel estimates to synthesize an antenna array from the plurality of geographically distributed access points, and the access-point weights are used to implement spatial multiplexing.

RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.14/789,949, filed Jul. 1, 2015, now U.S. Pat. No. 10,355,720, which is aContinuation-in-Part of U.S. patent application Ser. No. 13/116,984,filed May 26, 2011, now U.S. Pat. No. 10,014,882, which is aContinuation-in-Part of U.S. patent application Ser. No. 12/328,917,filed Dec. 5, 2008, now U.S. Pat. No. 7,965,761, which is a Divisionalof U.S. patent application Ser. No. 11/621,014 filed Jan. 8, 2007, nowU.S. Pat. No. 7,593,449, which is a Divisional of U.S. patentapplication Ser. No. 10/131,163 filed Apr. 24, 2002, now U.S. Pat. No.7,430,257, which claims priority to U.S. Provisional Application60/286,850, filed Apr. 26, 2001, all of which are expressly incorporatedby reference in their entireties.

BACKGROUND I. Field

The present invention relates generally to wireless communicationnetworks, and more specifically to cooperative signal processing betweenwireless transceivers.

II. Background

The background description includes information that may be useful inunderstanding the present inventive subject matter. It is not anadmission that any of the information provided herein is prior art orrelevant to the presently claimed inventive subject matter, or that anypublication, specifically or implicitly referenced, is prior art.

Communication over the spatial modes of a point-to-point MIMO channelwas developed in the early 90s [e.g., S. J. Shattil, U.S. Pat. No.6,211,671] then gradually extended to multi-user (MU-) MIMO channels[e.g., S. J. Shattil, U.S. Pat. No. 6,008,760].

In a conventional cellular communication system, transmissions todifferent users are formed independently. Hence, the transmission to oneuser can act as interference to other users. Because the system formsthe transmission to each user independently, the system has no way ofknowing how a transmission to a particular user will impact other usersin the vicinity. As a result, interference between cells is a mainfactor limiting the performance of current cellular systems. For usersnear a cell boundary, inter-cell interference is especially problematic.

Fading and interference are the two key challenges faced by designers ofmobile communication systems. While fading puts limits on the coverageand reliability of any point-to-point wireless connection, e.g., betweena base station and a mobile terminal, interference in prior-art networksrestricts the reusability of the spectral resource (time, frequencyslots, codes, etc.) in space, thus limiting the overall spectralefficiency expressed in bits/sec/Hz/base station.

The conventional approach to interference mitigation is spatial reusepartitioning, which prevents any spectral resource from being re-usedwithin a certain cluster of cells. Typically, the frequency re-usefactor is much less than unity such that the level of co-channelinterference is low. Thus, interference is controlled by fixing thefrequency reuse pattern and the maximum power spectral density levels ofeach base station. Some CDMA systems allow for full frequency re-use ineach cell, but at the expense of severe interference at the cell edge,resulting in a significant data rate drop at the terminals and a stronglack of fairness across cell users. Some interference mitigation can beachieved via limited inter-cell coordination, such as soft handovertechniques. Inter-cell interference is typically treated as noise at thereceiver side and is handled by resorting to improved point-to-pointcommunications between the base station and the mobile station usingefficient coding and/or single-link multiple-antenna techniques.

Some of the proposals for increasing the capacity of cellular networksinclude using more spectrum, increasing the number of transmit/receiveantennas on each station, using dedicated beams to serve users, andmicro-cell deployment. However, none of these approaches adequatelyaddress inter-cell interference, which is a primary bottleneck forspectral efficiency.

In the traditional cellular architecture, each base station onlyconnects to a fixed number of sector antennas that cover a small areaand only provide transmission/reception in its coverage area. Ideally,in such networks, the coverage areas of different base stations do notsubstantially overlap, as the system capacity is limited byinterference. In these networks, interference makes it difficult toimprove spectrum efficiency and network capacity. Another drawback totraditional cellular systems is that the base stations are built onproprietary platforms as a vertical solution.

Operators of prior-art cellular systems are faced with many challenges.For example, the high complexity of traditional base stations requirescostly initial investment, site support, site rental, and managementsupport. Building more base station sites imposes substantialinfrastructure and operational expenses on the network operator.Furthermore, since the base stations can't share processing power witheach other, network energy efficiency, processing efficiency, andinfrastructure utilization efficiency are low because the averagenetwork load is typically far lower than the peak load. Specifically,each base station's processing capability can only benefit the activeusers in its cell. Thus, a base station's processing capability iswasted when the network load within its cell is low, while at othertimes it may be oversubscribed. Also, an idle or lightly loaded basestation consumes almost as much power as it does under peak loads.

These and other drawbacks of the prior art can be reduced or eliminatedby exemplary aspects of the disclosure.

As explained above, prior-art broadband wireless technologies areband-limited or interference-limited, meaning that their spectralefficiency reaches an upper limit set by the laws of Physics, such asindicated by the Shannon formulas. While the spatial domain adds anotherdimension to exploit via cell planning and sectoring, increasing thecell density (e.g., micro-cells, pico-cells, femto-cells) beyond acertain point fails to mitigate the performance decline as more usersdemand services. This is because smaller cells result in increasedinter-cell interference, which establishes a practical upper bound forcell density. While the spectral efficiency of prior-art technologies islimited by the laws of Physics, the demand for data bandwidth keepsgrowing. As a result, today's cellular networks are already experiencingdeclining data rates per user.

Thus, there is a compelling need in the broadband wireless industry forsystems and methods of wireless communications in which networkperformance is not hard-limited by the laws of Physics, but ratherincreases according to advances in computer processing technologies,such as indicated by Moore's law. Only systems and methods such asdisclosed herein can meet the growing demands for broadband wirelessdata services.

SUMMARY

Aspects of the disclosure describe cooperative-MIMO processing whichcomprise MIMO processing wherein the multiple input (MI) comprisesdownlink transmissions from multiple base transceiver stations and themultiple output (MO) comprises uplink transmissions to multiple basetransceiver stations. Aspects of the disclosure also indicate thatcooperative-MIMO processing can employ user equipment (UEs). Inaccordance with some aspects, combinations of base transceiver stationsand UEs are configured for cooperative-MIMO processing.

In accordance with the deficiencies of the prior art, some aspects ofthe disclosure can eliminate problems due to inter-cell interferencenear cell boundaries by simply eliminating the cell boundaries. Forexample, unlike soft hand-off in which two base stations merely employthe same radio channel to serve a handset at a cell boundary,geographically distributed base stations can be coordinated to functiontogether as a distributed antenna system with overlapping coverage areasand configured to perform subspace antenna array processing. Sincesubspace antenna array transmissions can produce constructive anddestructive interference zones (i.e., amplified-signal andcancelled-signal zones) in a rich scattering environment, provisioningof radio resources in accordance with networks and methods disclosedherein can benefit from types of spatial reuse that far outperformcellular-based (e.g., honeycomb) spatial reuse schemes that rely onsignal attenuation via path loss.

Whereas prior-art cellular systems strive to reduce inter-cell andintra-cell interference, aspects of the disclosure exploit interferenceto achieve substantial performance gains. Some exemplary aspectsdramatically improve system performance, including throughput, coverage,signal quality, and spectral efficiency, by exploiting inter-cell(and/or intra-cell) interference. Furthermore, since capacity in adownlink multi-user MIMO system depends on the number of transmittingantennas, coordinating multiple geographically distributed basetransceiver stations to cooperatively perform multi-user MIMO processingcan effectively increase the number of transmitting antennas, and thus,downlink system capacity (which can translate into a combination ofserving more users, increasing data rates per user, and improvingquality metrics of the communication links). Some aspects of thedisclosure produce similar benefits for uplink performance in amulti-user MIMO system.

In some aspects, radio transceivers operating in networks disclosedherein can perform either or both client and server operations. By wayof example, a UE may be configured to operate as a base transceiverantenna in a Cooperative-MIMO configuration with one or more basetransceiver systems, thereby increasing the rank of the channel matrix,which enables more subspace channels to be employed in the uplink and/ordownlink. The UE may be coordinated with the one or more basetransceiver systems via a fronthaul network, including the radio accessnetwork (e.g., the WWAN). By way of example, a base transceiver systemmay be configured to operate as a UE in a local group of UEs organizedin a Cooperative-MIMO configuration. The base transceiver can beconfigured to communicate with the local group via a local area network(e.g., a UE fronthaul network used to coordinate the group of UEs) inorder to increase the rank of the channel matrix employed for uplinkand/or downlink subspace processing.

Aspects of the disclosure may be provided for achieving a large numberof objectives and applications which are too numerous to list herein.Therefore, only some of the objects and advantages of exemplary aspectsare discussed in the Summary and in the Detailed Description. In someaspects of the disclosure, interference is dealt with using cooperativeMIMO so as to increase the number of co-channel links that can coexistwith acceptable quality of service. For example, in the high-SNR regime,this figure of merit corresponds to the maximum number of concurrentinterference-free transmissions, which is referred to as themultiplexing gain of the network, or the number of degrees of freedom inthe information-theoretic terminology.

Some aspects of the disclosure provide various types ofinterference-aware multi-cell coordination. For example, in someaspects, base stations no longer tune separately their physical andlink/MAC layer parameters (power level, time slot, subcarrier usage,beamforming coefficients, etc.) or decode independently of one another,but instead coordinate their coding and/or decoding operations on thebasis of global channel state and user data information exchanged overfronthaul (e.g., backhaul) links among multiple cells. Coordinationprotocols can exploit existing fronthaul links (e.g., WiMax, 4G LTE,optical fiber) or may require a design upgrade to accommodate additionaloverhead. There are various degrees of cooperation, offering a trade-offbetween performance gains and the amount of overhead placed on fronthauland/or other channels, including over-the-air feedback channels.

In some aspects of the disclosure, such as disclosed in the '850application, certain network control functions are performed in acooperative fashion by a central processing unit for a set ofcooperating base transceiver stations. The central processing unit canbe incorporated in one of the cooperating base transceiver stations,which can be connected with any of the other cooperating basetransceiver stations via a low-latency, high-capacity fronthaul network.Various network control functions can be performed by the centralprocessing unit, including resource allocation (e.g., scheduling) andpower control.

In some aspects of the disclosure, antenna array processing performed bythe central processing unit can mitigate inter-cell interference causedby simultaneous transmissions scheduled on the same frequency resourceby nearby base transceiver stations. In one aspect, the centralprocessing unit coordinates beamforming (e.g., calculatesarray-processing weights from channel measurements and coordinatestransmissions of the base transceiver stations) such that one basetransceiver station provides for coherent combining of its transmissionsat a target UE while at least one other base transceiver stationproduces transmissions that destructively combine at the target UE. Inanother aspect, the central processing unit is configured to performjoint processing of subspace signals for coordinated multipointtransmissions, wherein multiple base transceiver stations serve a targetUE with subspace-coded transmissions. For example, multiple basetransceiver stations can be provided with subspace pre-coding weightscalculated from channel measurements, and their transmissions can becoordinated such that the set of base transceiver stations functionsjointly as an array of transmitters that produces multiplenon-interfering subspace channels. Specifically, first portions ofsubspace-coded transmissions from antennas on multiple ones of the basetransceiver stations combine coherently at the target UE to produce atleast a first data stream, whereas at least second portions of thesubspace-coded transmissions from different ones of the base transceiverstations combine destructively at the target UE to cancel at least asecond data stream, wherein the at least second data stream is intendedfor at least one other UE. Subspace processing in the disclosed aspectscan include various techniques, including, but not limited to, maximumratio combining (MRC), zero-forcing (ZF), and minimum mean square error(MMSE) techniques.

In one aspect of the disclosure, a network of M connected J-antenna basestations can serve a total of MJ terminals in an interference-freemanner simultaneously, regardless of how strong the interference is. Toachieve this remarkable result, multi-user spatial pre-coding anddecoding can be employed on the downlink and uplink, respectively.

In accordance with some aspects of the disclosure, a cloud radio accessnetwork (C-RAN) comprises multiple geographically distributed basetransceiver stations, a high-bandwidth low-latency optical transportnetwork (e.g., a fronthaul network), and a central processor. The basetransceiver stations are connected to the central processor via thefronthaul network. Furthermore, the central processor may comprisedistributed computing resources. For example, the central processor maycomprise (or be communicatively coupled to) high-performanceprogrammable processors and real-time virtualization technology. Someaspects employ a software defined radio (SDR) platform.

In one aspect of the disclosure, a C-RAN system comprises basetransceiver stations that operate solely as radio units (e.g., remoteradio heads), while the RAN baseband processing is performed at acentral processor within the operator's network. Fronthaul links, suchas fiber optic links or wireless links, connect each base transceiverstation to the central processor. The centralization of both uplink anddownlink baseband processing at the central processor enables manybenefits, including allowing the central processor to performcancellation of the downlink-uplink interference, since the downlinksignal is known at the central processor.

Centralized signal processing disclosed herein greatly reduces theamount of base transceiver equipment needed to cover the same area.Cooperative processing, such as Cooperative-MIMO in a distributedantenna system, provides higher spectrum efficiency. Real-time cloudinfrastructure (which can be based on an open platform and utilize basestation virtualization) enables processing aggregation and dynamicresource allocation, reducing the power consumption and increasing theinfrastructure utilization rate. This network architecture isadvantageous for LTE-Advanced, which requires tight coordination betweenneighboring cells, as such coordination is facilitated at the centralprocessor where RAN baseband functions of the base transceiver stationsare pooled.

In another aspect of the disclosure, methods for providing C-RANcommunications comprise performing RAN baseband processing at a centralprocessor, while a distributed antenna system comprising a network ofgeographically distributed base transceiver stations acts solely asdown-converters in the uplink and up-converters in the downlink. Thefronthaul links carry baseband information. In one aspect, in theuplink, UE signals received by the base transceiver stations areforwarded to the central processor, which performs joint decoding. Inanother aspect, in the downlink, the central processor performspre-coding and then communicates the resulting baseband signals via thefronthaul links to the base transceiver stations. Each base transceiverstation simply up-converts the baseband signal and transmits it to theUEs.

With centralized processing of the C-RAN architecture, power consumptiondue to air conditioning and other equipment at the base transceiversites can be reduced. In many aspects, the distance from the basetransceiver stations to the UEs can be decreased, since Cooperative-MIMOprocessing can mitigate the effects of interference between basetransceiver stations, allowing for a much higher density of basetransceiver stations. With smaller cells, the power required for signaltransmission is reduced, which can decrease power consumption in boththe RAN and the UEs. Furthermore, because baseband processing isimplemented via a shared resource among a large number of basetransceiver stations, more efficient utilization of processing resourcesand lower power consumption can be achieved.

In aspects of the disclosure, the base station baseband processors andsite support equipment are aggregated in a centralized location. Thiscentralized management and operation can be far more efficient thanmanaging a large number of base station sites in a traditional RANnetwork. If each base transceiver station's functionality is simpler,the size, cost, and power consumption can be reduced. Thus, basetransceiver stations can be smaller, less expensive, and easier todeploy with minimum site support and management requirements.Centralized operation also facilitates sharing of the control signaling,traffic data, and channel state information in the system, which canenable joint processing and scheduling to mitigate inter-cellinterference and improve spectral efficiency.

In some aspects of the disclosure relating to non-transitorycomputer-readable medium with instructions stored thereon, the term“virtual” is used. While virtualization typically refers to theabstraction of computer resources in which the physical characteristicsof a computing platform are hidden from users and/or applications, theterm, virtual, can also relate to an abstraction of a networkconfiguration wherein signal-processing functions do not require certaindetails of a distributed antenna system. In some aspects, portions ofmethods and systems that provide for channel characterization andcalculating antenna array weights for subspace multiplexing and/ordemultiplexing do not require certain information about the distributedantenna system. For example, some of the signal-processing functions canbe independent of whether the system comprises a conventional antennaarray or a plurality of separate RAN transceivers communicativelycoupled together via a fronthaul network. Some signal-processingfunctions can be independent of whether they are performed at a basetransceiver station or at a central processor to which the basetransceiver station is communicatively coupled. This enables MIMO andother baseband processing to be performed at the central processor.

In some aspects of the disclosure, central processing comprisesdistributed computing. Thus, a network operator can dynamically allocateprocessing resources within a centralized baseband pool to differentvirtualized base stations and different air interface standards. Thisallows the operator to efficiently support a variety of air interfacesand adjust to varying network loads across different geographical areas.Within a centralized baseband pool, physical layer processing resourcescan be efficiently managed and allocated via real time virtualization.Thus, a base station instance can be adapted through the flexibleresource combination, which can adjust, allocate, and re-allocateresources based on each virtualized base station's requirements in orderto meet its demands. This provides Cooperative-MIMO operations with therequired processing resources dynamically. Furthermore, centralizing thehardware platform can provide cost effectiveness for managing,upgrading, and expanding the base station network.

In accordance with some aspects of the disclosure, a plurality oftransmitting nodes is employed by a source node to build the dimensionof the subspace spanned by the coded transmissions. In one aspect, theplurality of transmitting nodes is selected to ensure that a set ofpre-coded transmissions is characterized by sufficient rank to allow adestination node to decode received signals. For example, selecting asufficient number of transmitting nodes and encoding (e.g., pre-coding)original data signals can produce a sufficient number of linearlyindependent (i.e., algebraically unique) combinations of the originaldata signals to permit the destination node(s) to resolve the originaldata signals. The transmitting nodes can be selected based on channelmeasurements and/or their geographic locations such as to ensure thattheir transmissions are uncorrelated. Each of the transmitting nodestransmits a subset of a total number (i.e., plurality) of subspace-codedcomponents and a corresponding code matrix, wherein at least one of thetransmitting nodes has a rank that is insufficient for decoding theplurality of subspace coded components (e.g., a destination node needsto receive signals from a plurality of the transmitting nodes in orderto achieve sufficient rank for decoding the received signals). Thecorresponding code matrix can take the form of a preamble (or header)that comprises the code matrix. When the codes comprise channel-specificcodes based on the naturally random channel, then the codes compriserandom codes.

As disclosed in some aspects herein, the transmitting nodes can functionas routers, relays, repeaters, etc., configured to encode receivedsignals prior to retransmission or simply pass through received signalsprior to retransmission. In some aspects, the transmitting nodes cancombine multiple signals to be transmitted. In some aspects, thenaturally random channel provides random linear coding to transmissions,such as when transmitting nodes are selected to produce transmissionswith uncorrelated multipath effects (e.g., fading).

In accordance with some aspects of the disclosure, a destination nodecan employ a plurality of receiving nodes to cooperatively receive aplurality of subspace-coded components and their corresponding codevectors, wherein the rank of at least one of the receiving nodes isinsufficient for decoding the coded components. Thus, receiving nodescan function as routers, relays, repeaters, etc. The destination nodebuilds up the dimension of the subspace spanned by code vectors itcollects from the receiving nodes so it can decode the coded components.For example, the destination node can receive signals from multiplereceiving nodes in order to decode the subspace-coded components. Thereceiving nodes can be selected to provide uncorrelated channels.

As disclosed herein, intervening nodes can function as either or bothtransmitting nodes and receiving nodes. Whereas in conventional routing,intervening nodes simply replicate and forward their received packets,cooperative network coding (such as disclosed in the '163 application)enables relay nodes to combine information received from multiple linksfor subsequent transmissions. The '163 application discloses varioustypes of linear network codes, including polyphase codes derived from adiscrete Fourier transform and random codes, such as derived from thenatural randomness of wireless multipath channels, and combinationsthereof.

In some aspects of the disclosure, assigned wireless network channels(such as network channels allocated to a particular frequency band andtime interval) are reused. For example, cooperative subspace processing(e.g., Cooperative-MIMO) generates a plurality of parallel subspacechannels that can simultaneously occupy the same spectral resource. IfOFDM is employed, this means that multiple parallel spatial subchannelscan occupy the same set of OFDM subcarriers, or tones. In some aspects,cooperative subspace processing provides for communicatively couplingtogether multiple geographically distributed transceivers (e.g., basetransceiver stations and/or wireless client devices) via a fronthaulnetwork to enable joint processing operations.

In some aspects of the disclosure, a network channel is allocated to atransceiver operating in a first network, wherein the transceiver ispart of a group of transceivers comprising a second network. The networkchannel is reused by the group of transceivers for communicating in thesecond network in a manner that avoids interfering with the firstnetwork. By way of example, the group of transceivers employs spatialmultiplexing, such as cooperative subspace processing, to mitigateinterference between the first network and the second network.

In one aspect of the disclosure, a transceiver employs a channelallocation for a first communication link in a first group oftransceivers comprising a first network. A second group of transceiversthat is different from the first group but comprises the transceiverreuses the channel allocation for communicating in at least a secondcommunication link. The second group is configured to employ any ofvarious interference-mitigation techniques that permit the reuse of thechannel allocation while minimizing co-channel interference with thefirst network. In some aspects, the second group is configured to employinterference-mitigation techniques that mitigate the effects ofco-channel interference in the second link due to transmissions in thefirst link.

By way of example, if the channel allocation is for a downlink channel,the second group can perform either or both transmit-side andreceive-side spatial multiplexing to cancel interference fromtransmissions in the first link that could interfere with one or morereceivers in the second link. If the channel allocation is for an uplinkchannel, the second group can perform transmit-side spatial multiplexingto cancel interference from transmissions in the second link that couldinterfere with receivers employing the first link. The second group canperform either or both transmit-side and receive-side spatialmultiplexing to cancel interference due to transmissions in the firstlink that could interfere with one or more receivers employing thesecond link.

As described throughout the '163 application, aspects disclosed hereincan be implemented in a cloud-based SDR platform.

Groupings of alternative elements or aspect of the disclosed subjectmatter disclosed herein are not to be construed as limitations. Eachgroup member can be referred to and claimed individually or in anycombination with other members of the group or other elements foundherein. One or more members of a group can be included in, or deletedfrom, a group for reasons of convenience and/or patentability. When anysuch inclusion or deletion occurs, the specification is herein deemed tocontain the group as modified, thus fulfilling the written descriptionof all Markush groups used in the appended claims.

All methods described herein can be performed in any suitable orderunless otherwise indicated herein or otherwise clearly contradicted bycontext. The use of any and all examples, or exemplary language (e.g.,“such as”) provided with respect to certain embodiments herein isintended merely to better illuminate the inventive subject matter anddoes not pose a limitation on the scope of the inventive subject matterotherwise claimed. No language in the specification should be construedas indicating any non-claimed element as essential to the practice ofthe inventive subject matter.

Additional features and advantages of the invention will be set forth inthe description which follows, and in part will be obvious from thedescription, or may be learned by practice of the invention. Thefeatures and advantages of the invention may be realized and obtained bymeans of the instruments and combinations particularly pointed out inthe appended claims. These and other features of the invention willbecome more fully apparent from the following description and appendedclaims, or may be learned by the practice of the invention as set forthherein.

BRIEF DESCRIPTION OF THE DRAWINGS

Flow charts depicting disclosed methods comprise “processing blocks” or“steps” may represent computer software instructions or groups ofinstructions. Alternatively, the processing blocks or steps mayrepresent steps performed by functionally equivalent circuits, such as adigital signal processor or an application specific integrated circuit(ASIC). The flow diagrams do not depict the syntax of any particularprogramming language. Rather, the flow diagrams illustrate thefunctional information one of ordinary skill in the art requires tofabricate circuits or to generate computer software to perform theprocessing required in accordance with the present disclosure. It shouldbe noted that many routine program elements, such as initialization ofloops and variables and the use of temporary variables are not shown. Itwill be appreciated by those of ordinary skill in the art that unlessotherwise indicated herein, the particular sequence of steps describedis illustrative only and can be varied. Unless otherwise stated, thesteps described below are unordered, meaning that the steps can beperformed in any convenient or desirable order.

FIG. 1 is a block diagram of a communication system architecture inaccordance with an exemplary aspect of the invention.

FIG. 2 illustrates a network configuration for super-array processing inaccordance with some aspects of the invention.

FIG. 3A is a flow diagram of a super-array processing method inaccordance with an aspect of the invention.

FIG. 3B is a flow diagram of a super-array processing method inaccordance with an aspect of the invention in which channel informationis estimated from measurements of reference signals transmitted by theUEs. The reciprocal nature of the channel can enable channel estimationof received uplink signals to be used to calculate pre-coding for thedownlink channel.

FIGS. 4A and 4B are flow diagrams depicting spatial demultiplexingimplemented via multi-cell MIMO cooperation in wireless networks.

FIG. 5 is a flow diagram depicting a method in accordance with an aspectof the disclosure in which multiple geographically distributedtransmission points are coupled to a central processor via a fronthaulnetwork, and the central processor calculates pre-coding weights forspatial multiplexing and coordinates the transmission points to transmitsubspace pre-coded downlink signals to multiple UEs.

FIG. 6 is a flow diagram depicting a method in accordance with an aspectof the disclosure in which multiple geographically distributedtransmission points are coupled to a central processor via a fronthaulnetwork, and the central processor is configured to perform spatialdemultiplexing of UE uplink transmissions received by the distributedtransmission points.

FIG. 7 is a flow diagram depicting messages passed between UEs, basetransceiver stations, and a central processor corresponding to asuper-array processing method.

FIG. 8 comprises pseudo-code that depicts data structures and processingfunctions that can be implemented by a computer processor programmed toperform methods, such as super-array processing methods, in accordancewith aspects of the disclosure.

FIG. 9 is a block diagram of a UE that can be configured to operate inaccordance with aspects of the disclosure.

FIG. 10 is a block diagram of a base transceiver station that can beconfigured to operate in accordance with aspects of the disclosure.

FIG. 11A is a block diagram of a central processor that can beconfigured to operate in accordance with aspects of the disclosure.

FIG. 11B is a block diagram that depicts a cloud-based software-definedradio, which can be implemented in accordance with many differentaspects of the disclosure.

FIG. 12 is a block diagram of a super-array processing system comprisinga central processor communicatively coupled to multiple geographicallydistributed base transceiver stations via a fronthaul network.

FIG. 13A is a flow diagram of a subspace processing method configured inaccordance with some aspects of the disclosure.

FIG. 13B is a flow diagram of a subspace processing method that employsdecision feedback configured in accordance with some aspects of thedisclosure.

FIGS. 14A and 14B are block diagrams that illustrates method andapparatus implementations of radio transceivers in accordance withaspects of the disclosure.

FIG. 15 is a block diagram of a transceiver in accordance with someaspects of the disclosure.

FIG. 16 is a block diagram depicting functional aspects of transceiversaccording to aspects of the disclosure.

FIG. 17 depicts a network comprising multiple geographically distributedbase transceiver stations communicatively coupled together via afronthaul network. The base transceiver stations are configurable tojointly process signals in a radio access channel that serves multipleUEs. In some aspects of the disclosure, at least one of the basetransceiver stations coordinates joint processing.

FIG. 18 depicts a cloud radio access network comprising multiplegeographically distributed base transceiver stations communicativelycoupled to a central processor via a fronthaul network, wherein thecentral processor comprises a distributed computing system. In suchaspects, combinations of central processing and distributed computingcan provide for pooling and virtualizing base station processing, suchas via an SDR.

FIG. 19 depicts a coordinated multipoint network wherein a plurality ofaccess points are communicatively coupled to a central processor via afronthaul network, and wherein at least some of the access points'signal processing functions (such as RAN baseband processing) are pooledat the central processor. Apparatus implementations corresponding tothis aspect of the disclosure include providing for relocating accesspoint baseband processing equipment to the central processor, which cangreatly reduce the capital expense and operating expense associated withthe access point network.

FIGS. 20A and 20B are flow charts depicting methods whereingeographically distributed access points perform RF processing in aradio access network and a central processor performs corresponding RANbaseband processing. In some aspects the corresponding RAN basebandprocessing is performed by a distributed computing system.

FIG. 21 depicts a network topology comprising a source node, adestination node, and a plurality of intervening nodes. This and othernetwork topologies shown herein depict some aspects of the disclosure,including cooperative-MIMO, cooperative subspace coding along multiplenetwork paths, simultaneously employing multiple network paths as asingle communication link, providing for reusing spectral resourcesacross multiple links, etc.

FIGS. 22A and 22B depict signal transmissions propagating in a networkwith multiple intervening nodes between a source node and a destinationnode. Selecting the intervening nodes as part of a transmit and/orreceive cooperative subspace processing operation can build the rank ofthe subspace coding matrix of coded signals propagating through thenetwork, thus providing a sufficient number of linearly independentcombination of original data to permit subspace demultiplexing at thedestination node.

FIG. 23A is a flow diagram that illustrates aspects of the disclosurepertaining to cooperative subspace multiplexing.

FIG. 23B is a flow diagram that illustrates aspects of the disclosurepertaining to cooperative subspace demultiplexing.

FIGS. 24A and 24B are block diagrams depicting transceiver apparatus andmethod aspects configured to perform routing and/or relaying.

FIGS. 25A and 25B are block diagrams that depicts channel reuse, such asmay be configured between a plurality of networks.

FIG. 26 depicts a cooperative-MIMO network configured to employ channelreuse.

FIG. 27 is a flow diagram that depicts channel reuse methods inaccordance with some aspects of the disclosure.

DETAILED DESCRIPTION

The terms “backhaul” and “fronthaul” can be used interchangeably in someaspects of the disclosure. A fronthaul is similar to a backhaul, which,at its simplest, links a radio access network to a wired (e.g., cable oroptical fiber) network. A fronthaul can comprise a backhaul, or aportion of a backhaul. For example, a fronthaul can comprise aconnection between one or more centralized controllers and remotestand-alone radio heads. A fronthaul connects a central processor tomultiple base transceiver stations. A fronthaul connects multiple basetransceiver stations together when one or more of the base transceiverstations functions as a central processor. As used herein, a fronthaulmay comprise a traditional backhaul network. For example, a fronthaulcan comprise at least a portion of S1 and/or X2 interfaces. A fronthaulmay be part of a base station network. In Pat. Appl. Ser. No.60/286,850, it is disclosed that a fronthaul can comprise optical fiber,wired, and/or radio networks. In one aspect of the disclosure,point-to-point fiber links provide high bandwidth and low latency. Inanother aspect, radio (e.g., microwave) links can provide high bandwidthand low latency, and can be substantially less expensive to implementthan fiber. Furthermore, wireless links enable mobile radios and/orother radio transceivers (e.g., remote radio equipment) to be networkedtogether via a radio fronthaul, such as disclosed in patent applicationSer. No. 10/131,163. Accordingly, a fronthaul can comprise anycombination of wireless, wired, and optical fiber links thatcommunicatively couple together a group of radio transceivers configuredto perform cooperative MIMO. Here, a group of radio transceivers is alsoreferred to as a “micro-cell” and a “pico-cell” in the '163 application,and as a “local group” and a “micro-network” in patent application Ser.No. 11/187,107, all of the patents and patent applications mentionedherein being incorporated by reference in their entireties.

Pre-coding is defined herein to comprise its ordinary and customermeaning known to those of ordinary skill in the art. By way of example,in the '163 application, pre-coding is described in the context ofantenna array transmission systems with the terms, “pre-transmissionprocessing,” “pre-distortion,” “channel compensation,” “transmitfiltering,” “spatial interferometry multiplexing,” and “subspaceprocessing.” The '163 application also discloses directive andretro-directive adaptation methods for calculating antenna array weightsfor transmission in a distributed antenna system. In one example,subspace pre-coding weights are calculated from measurements of receivedsignals, the measurements comprising channel state information.

User Equipment (UE), as used herein, may be fixed or mobile andcomprises any device used directly by an end user (or client device) tocommunicate in a radio access network. For example, a UE can be acellular handset, a laptop equipped with a mobile broadband adaptor, awearable computer, a PDA, a tablet, or any other user device configuredto communicate with a Wireless Wide Area Network (WWAN). A WWAN is alsoreferred to as a radio access network (RAN). A UE comprises an RFtransceiver for fixed and/or mobile clients receiving data streams overthe downlink channel of the WWAN and transmitting data via the WWAN'suplink (UL) channel. While a UE is defined in the Universal MobileTelecommunications System (UMTS) and 3GPP Long Term Evolution (LTE) asany device that connects to a base station NodeB or eNodeB as specifiedin the ETSI 125/136-series and 3GPP 25/36-series of specifications, UEsinclude equivalent devices, such as mobile stations in GSM systems andclient devices in other wireless networks. As used herein, a UE may alsobe referred to as a subscriber device, mobile terminal, user terminal,wireless terminal, subscriber terminal, client terminal, subscriberunit, mobile unit, subscriber device, mobile device, wireless device,client device, client terminal, client unit, mobile network device,mobile handset, wireless handset, or some other terminology indicating aWWAN-enabled client device.

In general, the various embodiments of the UE can include, but are notlimited to, cellular mobile devices, personal digital assistants (PDAs)having wireless communication capabilities, portable computers havingwireless communication capabilities, image capture devices such asdigital cameras having wireless communication capabilities, gamingdevices having wireless communication capabilities, music storage andplayback appliances having wireless communication capabilities, Internetappliances permitting wireless Internet access and browsing, as well asportable units or terminals that incorporate combinations of suchfunctions. Examples of UEs are provided in 3GPP technical specification(TS) 36.306, Release 8, the disclosure of which is incorporated hereinby reference in its entirety.

A Base Transceiver Station interfaces the fronthaul network with theWWAN channel. Base transceiver stations of one embodiment compriseaccess points consisting of a Digital-to-Analog Converter(DAC)/Analog-to-Digital Converter (ADC) and a radio frequency (RF) chainto convert the baseband signal to RF. A base transceiver stationcontains radio frequency transmitter(s) and receiver(s) forcommunicating directly with UEs. In some cases, the base transceiverstation is a simple RF transceiver equipped with a poweramplifier/antenna, and the RF signal is carried to the base transceiverstation via RF-over-fiber technology as disclosed in the '850 and '163applications. In other aspects, base transceiver stations are equippedto perform at least some RAN baseband processing operations, such asdisclosed in the '850 and '163 applications. Additional features andaspects of base transceiver stations are described throughout thedisclosure and in the aforementioned patent applications, which areincorporated by reference. As used herein, a base transceiver stationmay also be referred to as a base station, an access point, a NodeB, anevolved NodeB (eNodeB), or some other terminology. In accordance withsome aspects of the disclosure, a base transceiver station is a networknode.

A “network node” or “node,” as used herein, is an active electronicdevice that is communicatively connected to a network via one or moreconnectors and is configured for sending, receiving, and/or forwardinginformation over a communication channel. A node can have multiplenetwork connectors for a given network. For example, a node can havemultiple antennas. A single device, such as a base station or a userterminal, with multiple network connectors is a single node. In adistributed network, nodes can be clients, servers, and/or peers. A peercan sometimes serve as a client and sometimes as a server. Nodes caninclude super nodes, which route data for other networked devices aswell as themselves.

A Central Processor can include one or more servers interfacing theInternet (or other external networks) with the fronthaul. In ahierarchical network architecture, a central processor couples to thebase transceiver stations and provides coordination and control forthose stations. One or more base transceiver stations may function as acentral processor, such as in a flat network architecture. In an LTEnetwork, eNodeB(s) and/or access gateways can be configured to performcentral processor functions. In some aspects of the disclosure, networkcontrol functions typically performed by a central processor may beassigned to any of various nodes in the network, including UEs.

In some aspects of the disclosure, the central processor computes themulti-user MIMO baseband processing and sends pre-coded data togeographically distributed base transceiver stations for downlinktransmission. In some aspects, the central processor computes themulti-user MIMO baseband processing to provide spatial demultiplexing ofuplink signals received by the geographically distributed basetransceiver stations. In some aspects, the central processor cancomprise a particular type of base transceiver station designed forcertain specialized features, such as transmitting training signals fortime/frequency synchronization of the base transceiver stations and/orthe UEs, receiving/transmitting control information from/to the UEs,receiving the channel state information or channel quality informationfrom the UEs, etc. In some aspects, a central processor is also referredto as a central processing facility, a cloud computing center, a cloud,a data center, a data center cloud, a central controller, a radionetwork controller, or a central control hub. In some aspects, a centralprocessor can comprise multiple data centers.

Various aspects of the disclosure are described below. It should beapparent that the teachings herein may be embodied in a wide variety offorms and that any specific structure, function, or both being disclosedherein are merely representative. Based on the teachings herein oneskilled in the art should appreciate that an aspect disclosed herein maybe implemented independently of any other aspects and that two or moreof these aspects may be combined in various ways. For example, anapparatus may be implemented or a method may be practiced using anynumber of the aspects set forth herein. In addition, such an apparatusmay be implemented or such a method may be practiced using otherstructure, functionality, or structure and functionality in addition toor other than one or more of the aspects set forth herein.

The use of any and all examples, or exemplary language (e.g. “such as”)provided with respect to certain embodiments herein is intended merelyto better illuminate the invention and does not pose a limitation on thescope of the invention otherwise claimed. No language in thespecification should be construed as indicating any non-claimed elementessential to the practice of the invention. The word “exemplary” is usedherein to mean “serving as an example, instance, or illustration.” Anyembodiment or aspect described herein as “exemplary” is not necessarilyto be construed as preferred or advantageous over other embodiments oraspects.

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the invention. It should be understood, however, thatthe particular aspects shown and described herein are not intended tolimit the invention to any particular form, but rather, the invention isto cover all modifications, equivalents, and alternatives falling withinthe scope of the invention as defined by the claims.

FIG. 1 is a block diagram of a communication system architecture inaccordance with an exemplary aspect of the invention. A plurality N ofbase stations 101.1-101.N are communicatively coupled to a centralprocessing facility 110 (i.e., a central controller) via a communicationnetwork 105. Each base station 101.1-101.N comprises an antenna systemfor communicating with one or more mobile units (e.g., User Equipment)120.1-120.K. For example, the first base station 101.1 may comprise afirst antenna array comprising a plurality M₁ of antennas 102.1-102.M₁,and the N^(th) base station 101.N may comprise an N^(th) antenna arraycomprising a plurality M_(N) of antennas 104.1-104.M_(N). A plurality Kof mobile units 120.1, 120.2, and 120.K are shown, each having its ownantenna system 121.1, 121.2, and 121.K, respectively. Each antennasystem 121.1, 121.2, and 121.K may comprise one or more antennas. Thecommunication network 105 that communicatively couples the base stations101.1-101.N to the central processing facility 110 may comprise a fibernetwork, a cable (i.e., wired) network, a wireless network, or anycombination thereof.

In one aspect of the invention, the signal-processing architectureprovides base stations 101.1-101.N that are essentially “dumbterminals.” For example, many of the signal processing operationstypically performed at a base station 101.1-101.N may be transferred toa central processor (e.g., the central processing facility 110) that isconnected to the plurality of base stations 101.1-101.N. In some aspectsof the invention, a minimal amount of signal processing is performed ateach base station 101.1-101.N. For example, each base station101.1-101.N can perform basic signal-processing tasks, such asamplification, RF filtering, frequency conversion (e.g., frequencyup-conversion and/or frequency down-conversion), and/or other RFsignal-processing functions. After basic signal processing, signalsreceived by one or more antennas at each base station 101.1-101.N arecoupled into at least one communication channel (e.g., network 105)linked to the central processing facility 110. Functions of the basestation 101.1-101.N may be limited to cleaning up the received RFsignal, amplifying it, and processing the signal with respect tocoupling it into the network 105. Signals from different antennas102.1-102.M₁ and 104.1-104.M_(N) may be transmitted on differentchannels (e.g., on different waveguides), or they may be multiplexedonto the same channel (e.g., with respect to wavelength division, timedivision, frequency division, polarization division, subspace, phasespace, code division, mode division, directionality, etc.).

The central processing facility 110 processes each of the receivedsignals from the communication channel(s). For example, the centralprocessor 110 removes the individual signals from one or morecommunication channels. The removal process can include demultiplexingthe signals on the channel(s). In some aspects, the central processor110 frequency-converts the received signals to baseband, intermediate,or radio-frequency signals prior to processing. Beam-forming can beperformed in RF, IF, and/or after conversion to baseband.

Thus, in some aspects of the invention, by relocating most (or all) ofthe base station processing operations to the central processingfacility, the capital expenditures and operating costs of the radioaccess network can be greatly reduced. This can also facilitate rapidand less costly network upgrades and expansion. In one aspect, all theRF processing of the radio access network signals is performed at thebase transceiver stations, whereas baseband processing is performed atthe central processing facility. Baseband signals of the radio accessnetwork are communicated between the base transceiver stations and thecentral processing facility via a fronthaul radio network, some otherwireless network, waveguide (e.g., cable), an optical fiber network, ora combination thereof. RF processing of the fronthaul network signals(which is different than RF processing of the radio access networksignals) may be performed by the base transceiver stations and thecentral processing facility.

As depicted in FIG. 1, signal-processing operations performed at thecentral processing facility 110 can include spatial multiplexing and/orspatial demultiplexing 114.1, routing 114.2, and power control 114.3.The central processing facility 110 can be configured to performsuper-array processing. In one aspect of the invention, the centralprocessing facility 110 comprises a super array processing system 112.In some aspects of the invention, the super array processing system 112comprises one or more subsystems or modules, such as a spatialmultiplexing/demultiplexing system 114.1, a routing system (e.g.,router) 114.2, and a power control system 114.3.

In one aspect of the invention, the super array processing system 112comprises one or more general-purpose computers programmed to functionas a special-purpose computer configured to perform various aspects ofthe disclosure, such as Cooperative-MIMO processing in a distributedantenna system. In another aspect, the super array processing system 112comprises one or more special-purpose processors, such as integratedcircuits, discrete circuits, and/or other specialized hardwareconfigured to perform Cooperative-MIMO processing. As disclosed herein,a distributed computing system may be employed for implementing aspectsof the invention, such as spatial multiplexing, spatial demultiplexing,and/or baseband signal processing operations typically performed by basetransceiver stations. Such distributed computing systems may comprise anetwork of general-purpose computers (programmed to function as aspecial-purpose computers), such as servers, located in one or more datacenters. A distributed computing system may comprise a network ofspecial-purpose processors or a combination of special-purposeprocessors and general-purpose computers. Similarly, components ofsystem 112, as well as any other components, processors, systems, anddevices mentioned in the disclosure, may each comprise one or moregeneral-purpose computers, one or more special-purpose processors, orcombinations thereof, and may optionally comprise a distributedcomputing platform.

In accordance with some aspects of the invention, the centralizedarchitecture simplifies physical-layer system upgrades, since processingequipment used for multiple base stations 101.1-101.N resides at acommon location (i.e., the central processing facility 110). Upgrades toimproved modulation schemes, new receiver combining techniques, enhancedarray-processing, etc. can be provided at the central processingfacility 110 instead of at each base station 101.1-101.N. Similarly,adding or upgrading base station antennas (e.g., antennas 102.1-102.M₁and 104.1-104.M_(N)) is simplified since the antennas installed at eachbase station 101.1-101.N may simply be coupled to the central processingfacility 110 via the communication network 105. Adding base stations tothe network can be quick and less costly due to the low cost andcomplexity of each base station 101.1-101.N. Thus, any signal-processingupgrade associated with the base stations 101.1-101.N is performed atthe central processor 110.

In aspects of the invention that employ spatialmultiplexing/demultiplexing, the system capacity scales linearly withthe number of base station antennas (e.g., antennas 102.1-102M₁ and104.1-104.M_(N)) within range of the UEs 120.1-120.K. This is becausethe spatial multiplexing gain (i.e., the number of independent datastreams that can be sent concurrently over MIMO subchannels) isproportional to the number of antennas 102.1-102M₁ and 104.1-104.M_(N)serving the UEs 120.1-120.K.

Unlike conventional MIMO in which all of the transmitting antennasreside on a single device (e.g., a single base station), acooperative-MIMO transmitting system in accordance with aspects of thedisclosure comprises antennas residing on multiple devices (e.g., thebase stations 101.1-101.N). The super array processing system 112coordinates the base stations 101.1-101.N to synthesize an antennasystem comprising geographically distributed antennas, which providessuperior decorrelation of the transmission paths between transmittingantennas and receiving antennas in the MIMO system. Since MIMO antennasin prior-art systems reside on a single device, the length of the MIMOarray is only a few wavelengths, which is usually insufficient forproviding the spatial selectivity required to match the spatialmultiplexing gain to the number of transmitting antennas. Thus, inprior-art MIMO systems, the rank of the MIMO channel matrix is typicallyless than its dimension. Adding more antennas to a prior-art MIMO systemalmost always results in diminishing levels of return with respect tocapacity, whereas aspects of the invention solve this problem.

Since the system (depicted in FIG. 1) capacity scales linearly with thenumber of base station antennas, particularly if the antennas aregeographically distributed, it is advantageous to add more base stationsas UE density increases. There are several benefits to doing this.Unlike prior-art cellular systems, inter-cell interference is not aproblem in the radio access network depicted in FIG. 1. Rather, it isexploited for spatial multiplexing gain, whereas enormous effort is madein today's cellular systems to avoid inter-cell interference,particularly for smaller cells. In aspects of the invention, basestations can be added in the general vicinity of increased user densitywithout cell planning and extensive modifications to the radio accessnetwork. The central processing facility 110 immediately adapts to thenew radio access network architecture to add capacity to the targetarea.

Since optimal spatial multiplexing gain is typically achieved when SNRis high (e.g., close to a MIMO base transceiver station), distributedantenna systems disclosed herein can provide closely proximal basetransceivers for UEs throughout the coverage area that provide both highSNR and spatial selectivity. Unlike prior-art cellular systems in whicheach UE is linked to a single base station until it is handed off toanother base station, aspects of the invention provide for maintainingconcurrent links between the UE and multiple base stations throughoutthe UE's session. Thus, as the UE moves through the coverage area, itmaintains a consistently high SNR.

In other aspects of the invention, Cooperative-MIMO processing on theclient side can provide distributed antenna systems comprisingcooperating UEs that enable similar MIMO benefits.

In some aspects of the disclosure, all of the base station processing isperformed in the central processing facility 110 (which may be anoffsite data center as long as latency constraints are met) instead ofby the individual base stations 101.1-101.N. Thus, even at very highdensities of UEs, not only can all UEs remain connected to the network,but the UEs do not incur the overhead normally incurred by large numbersof UEs sharing one base station in a cell.

The central processing facility 110 could be scaled indefinitely toaccommodate increasing UE density and data demands. As the number of UEsand demand grows, not only is it easy to deploy additional basestations, as described above, but it is easy to expand the computingcapability in the central processing facility 110 to accommodate theadded base stations.

In accordance with some aspects of the invention disclosed in the '163application, a distributed (e.g., cloud) computing environment may beemployed to perform the base station processing. Also, the '163application discloses that the base station processing may be performedin an SDR. Thus, the implementation of the base station processing mayoccur entirely on general-purpose CPUs. One implementation of thecentral processing facility 110 in accordance with previously citeddisclosure could include a data center comprising multiple switches andgeneral-purpose servers that connect to the fronthaul network 105 viageneral-purpose digital links, such as 10 GbE or other links.

FIG. 2 illustrates a network configuration for super-array processing inaccordance with some aspects of the invention. In one aspect, multiplemobile units (e.g., UEs 120.1-120.K) are each serviced by multiple basestations (e.g., base stations 101.1-101.N) simultaneously. In one aspectof the invention, each base station 101.1-101.N comprises an antennaarray. For example, the first base station 101.1 comprises an M₁-elementarray 102.1-102.M₁, a second base station 101.2 comprises an M₂-elementarray 106.1-106.M₂, and the N^(th) base station 101.N comprises anM_(N)-element array 104.1-104.M_(N). In super-array processing, the basestation arrays (e.g., arrays 102.1-102.M₁, 106.1-106.M₂, and104.1-104.M_(N)) are configured to work together to exploit thepropagation environment, such as to enhance signal reception for eachmobile user 120.1-120.K, reduce power transmission requirements, andmitigate undesired interference.

For the purpose of describing an exemplary aspect of the invention,signals transmitted by mobile unit 120.1 may be received at multiplebase station antenna arrays (e.g., at base stations 101.1, 101.2, and101.N). Adapting each base station antenna beam pattern (e.g., beampatterns 201.1, 201.2, and 201.N) can enhance reception of signalstransmitted by each mobile unit 120.1-120.K. Transmissions to eachmobile unit 120.1-120.K can also be enhanced. For example, atransmission from base station 101.2 intended for mobile unit 120.2 maycause interference at mobile unit 120.1. However, this interference canbe mitigated by including a cancellation signal in the transmission frombase station 101.1 and/or base station 101.N. Since all of the basestations 101.1-101.N in this exemplary aspect are connected to thecentral processing facility 110, signal processing at this facility 110can be performed to allow multiple base stations to work together andthereby enhance the radio coverage, bandwidth efficiency, and powerefficiency.

With respect to each mobile unit 120.1-120.K, all of the interferingsignals transmitted by the multiple base transceiver stations101.1-101.N coherently combine to produce the exact waveform intendedfor that mobile unit with a high SNR (e.g., SINR). For example, firstportions of waveforms transmitted by the multiple base transceiverstations 101.1-101.N combine coherently at a first mobile unit (e.g.,101.1) to produce a first set of data signals intended for the firstmobile unit 101.1. Similarly, second portions of the transmittedwaveforms combine coherently at a second mobile unit (e.g., 101.2) toproduce a second set of data signals intended for the second mobile unit101.2. However, the first portions combine destructively to cancel atthe second mobile unit 101.2 and the second portions combinedestructively to cancel at the first mobile unit 101.1. In some aspectsof the invention, the high-SNR waveforms exist only in a small volumearound the corresponding intended mobile unit. Since these highlylocalized regions of high SNR are synthesized interference zones, thediameter of these three-dimensional regions (such as may be indicated bya full-width half-maximum amplitude or power) can be less than awavelength.

Propagation effects due to sparse antenna arrays are described in U.S.patent application Ser. No. 09/906,257, which is incorporated byreference in its entirety. When randomly spaced sources (orequivalently, sources transmitting random carrier frequencies) areemployed, interference patterns (i.e., superpositions of the transmittedsignals) away from the main lobe (i.e., where signals are configured tocombine coherently, or in phase) tend to have little variation betweenminima and maxima, particularly when many sources (or frequencies) areemployed.

In the spatial dimensions, a rich scattering environment can provide alarge number of effective sources (i.e., each scatterer is an effectivesource). It is anticipated that some aspects of the invention may employvery large numbers of transmitters to generate signals that coherentlycombine in 3-dimensional space at a desired receiver(s). When very largenumbers (e.g., hundreds or more) of transmitters and/or effectivesources are employed, the signal amplitude (or power) can fall offdramatically at a short distance (even a fraction of a wavelength) fromthe superposition peak. The signal levels can remain at a consistentlylow SNR throughout 3-dimensional space except, perhaps, very close tothe transmitters. With a sufficiently large number of transmitters, itmay be possible to transmit signals from each transmitter that are solow in power that the signals intended for a particular user device areindistinguishable from background noise throughout almost all of thecoverage area except in a small volume at the user device where theycoherently combine. Thus, some aspects of the invention can provide atype of physical-layer low probability of interception/low probabilityof detection (LPI/LPD) benefit due to spatial processing that isanalogous to LPI/LPD benefits of ultra-wideband signals. Such LPI/LPDbenefits can enhance security in wireless networks.

Array processing can be performed at the central processor 110 to adapttransmission and reception beam patterns to improve one or moreoperating criteria, such as signal-to-noise, signal-to-noise plusinterference, probability of error, bit error rate, etc. Various aspectsinclude the use of known training sequences and pilot signals, as wellas blind adaptive techniques. Open-loop and/or closed-loop feedbacktechniques can be used.

In one aspect, each UE may be assigned an orthogonal uplink pilot.However, the maximum number of orthogonal pilots is limited by theduration of the coherence interval divided by the channel delay spread.Thus, aspects of the invention may employ any of various channelestimation algorithms, such as blind techniques, that circumvent the useof pilots altogether. By way of example, the '163, '854, and '107applications disclose blind techniques that jointly estimate thechannels and the payload data.

Even though the propagation channel is reciprocal (between uplink anddownlink in time-division duplex systems), the RF front-ends in the basetransceivers and UEs may not be reciprocal between the uplink anddownlink. Accordingly, calibration of the hardware to ensure reciprocitymay be performed, such as disclosed in the '163 application.

The array-processing aspects of the invention can also be used inconjunction with control of other system operating parameters,including, but not limited to, power control, throughput, bandwidth,channel coding (e.g., convolutional, block, trellis, etc.), andfrequency band scheduling. In one aspect, the system reduces thetransmit power of a mobile unit when array processing enhances thesignal-to-noise-plus-interference of that unit's radio link. In anotheraspect, the level of array processing is adjusted with respect to somequality factor associated with each unit. For example, array processingmay be performed only for units that exceed a certain degree of signaldegradation, require a certain amount of throughput, or have apredetermined quality-of-service level (QOS). Array processing can beused for data links in a system that provides data and voice services,since digital links require a higher QOS. Array processing can be usedto compensate for signal-quality degradation for units assigned tointerfering channels.

It should be appreciated that signal processing at the centralprocessing facility 110 may be performed by multiple computer processorsvia distributed computing (e.g., cloud computing) such as disclosed inthe '163 application. In some aspects, the base station signalprocessing at the central processing facility 110 can be implemented ina real-time SDR to provide for software-defined networks that enablemore dynamic organization of resources, such as disclosed in the '163application. The central processor 110 may comprise one or more serversin a data center configured to compute baseband waveforms using an SDR,such as described in the '163 application.

Since multiple base transceiver stations 101.1-101.N are employed toserve each UE 120.1-120.K via Cooperative-MIMO subspace processing, itis advantageous for the coverage areas of base transceiver stations101.1-101.N employing the same spectral resources to overlap. This iscontrary to how cellular base stations are positioned in a conventionalcellular network. Prior-art base stations conform to a cellular layoutthat is carefully planned to minimize transmission overlap. However,aspects of the disclosure are not constrained to such cell plans becausesubspace processing can produce constructive and destructiveinterference zones throughout the radio access network's coverage areato enable spectral reuse, potentially for very large numbers of UEs,even UEs that are in close proximity to each other (e.g., on the orderof a few wavelengths, or even less). This enables universal spectralreuse while facilitating deployment of the radio access networkinfrastructure. In some aspects, the base transceiver stations101.1-101.N can be placed pseudo-randomly throughout the radio accessnetwork, such as to take advantage of locations that are convenientand/or less costly, and with less concern about coverage area and thepresence of obstructions in the propagation environment.

In some aspects, since each UE 120.1-120.K is concurrently served bymultiple base transceiver stations 101.1-101.N with overlapping coverageareas, a failure of a small number of base transceiver stations101.1-101.N is less likely to cause a service disruption. Rather, thespatial multiplexing/demultiplexing 114.1 can adapt to changes in theconfiguration of the base transceiver stations 101.1-101.N, such as toensure uninterrupted service.

The spatial multiplexing/demultiplexing 114.1 can perform variousspatial processing techniques, including (but not limited to) ZF, MMSE,MRC, and/or successive interference cancellation. In some aspects, MRCcan offer certain advantages due to the ease in which it can beimplemented in a distributed manner and its computational simplicity(e.g., when used for demultiplexing, received uplink signals can bemultiplied by the conjugate channel responses, and pre-coding downlinktransmissions is similarly simplified). The combination of the MRCreceiver (for the uplink) and its counterpart, maximum ratio pre-coding(for the downlink) comprise matched filtering, which is disclosed in the'163 and '854 applications. MRC can be advantageous when channelresponses associated with different terminals are substantiallyuncorrelated.

As disclosed in the '163 application, the fronthaul network 105 can takevarious forms, including a mesh architecture. Since at least some of thefronthaul links 105 can be wireless (such as disclosed in the '850application), and given that the base transceiver stations 101.1-101.Ncan comprise remote radio heads (or other simple radio transceivers), asdisclosed in the '850 application, the base transceiver station101.1-101.N hardware can be a fraction of the cost of prior-art basestations and can be deployed more quickly. Furthermore, as disclosed inthe '163, '854, and '107 applications, UEs 120.1-120.K and other devices(not shown) in the radio access network can function as base transceiverstations, such as to dynamically adapt to increased network loads and/orincreased UE density, compensate for base station outages, and/or expandthe coverage area.

FIG. 3A is a flow diagram of a super-array processing method inaccordance with an aspect of the invention. A plurality of basetransceiver stations (e.g., transmission points, or access points) isconfigured to transmit reference signals 301, which are measured by UEsto calculate channel state information 302. For example, the '850application discloses that reference signals, which include knowntraining sequences and pilot signals, are transmitted, and a channelmodel is developed by a receiver upon receiving the transmittedreference signals. The channel state information can comprise channelinformation relative to multiple base station antennas residing onmultiple geographically distributed base stations.

The UEs feedback the channel state information to the transmissionpoints 304, and the transmission points and/or the central processorcalculate pre-coding weights 305 therefrom. The '850 applicationdiscloses that open-loop and/or closed-loop feedback may be employed.While channel state information can comprise quantized channelestimates, channel state information can comprise alternativeindicators, such as codewords. In some aspects of the invention, such asdisclosed in the '850 application, step 305 comprises selecting UE's forwhich array processing is to be performed, wherein only UE's having apredetermined quality-of-service level are selected. In some aspectsdisclosed in the '850 application, different levels of array processingmay be performed, the level of array processing being selected withrespect to a quality factor associated with each UE.

Multiple transmission points are coordinated by the central processor totransmit the pre-coded data 307 to each UE. In some aspects of theinvention, such as in accordance with the disclosure of the '163application, step 305 and/or 307 comprises selecting a portion of thenetwork to serve a particular UE. For example, a predetermined set oftransmission points is selected to process transmissions to a particularUE based on received pilot signal power. Upon receiving thetransmissions, each UE demodulates the received signals 308. Since UE'smay comprise antenna arrays, such as disclosed in the '850 application,step 308 may comprise array processing, including MIMO processing.

In accordance with one aspect of the invention disclosed in the '163application, network processing functions are computed by a plurality ofspatially separated processors. For example, the central processor canbe replaced by a distributed computing system. The distributed computingsystem can comprise a plurality of transmission points. In some aspects,the distributed computing system can comprise UE's, repeaters, and/orother network equipment.

In accordance with aspects disclosed in the '850 application,super-array processing comprises a coordinated multipoint technologywhich sends and receives signals from multiple sectors or cells to agiven UE. By coordinating transmission among multiple cells,interference from other cells can be reduced and the power of thedesired signal can be increased.

In one aspect of the invention, signaling over a fronthaul network canbe used between base stations (e.g., eNodeB's) to coordinate amongcells. In another aspect of the invention, multiple remote radioequipments (RREs) are connected via an optical fiber fronthaul carryinga baseband signal between cells and a central eNodeB, which performs theRAN baseband signal processing and control, so the radio resourcesbetween the cells can be controlled at the central eNodeB. Other aspectsof the invention include combinations of distributed control based onindependent eNodeB configurations and centralized control based on RREconfigurations.

FIG. 3B is a flow diagram of a super-array processing method inaccordance with an aspect of the invention in which channel informationis estimated from measurements of reference signals transmitted by theUEs. This exemplary method can be useful when time division duplexing(TDD) is employed, such as wherein the uplink and downlink channelsassigned to each UE share the same frequency band. For estimation ofchannels at the transmitter in TDD networks, one can rely on thereciprocity of the uplink and downlink channels so that channelestimation on the uplink can be used for downlink transmission.

In one aspect of the invention, each UE transmits a known referencesignal 311, such as one or more known training sequences and/or pilotsignals, which are described in the '850 application. The transmittedreference signals are received by antennas of multiple basetransceivers, and the channel state information is measured 312 by thebase transceiver stations and/or at least one central processor. Asdisclosed in the '850 application, the channel state information cancomprise frequency-domain channel state information. In one aspect,measured channel state information is coupled by the base transceiverstations to the central processor to be used for calculating pre-codingweights 314. In accordance with another aspect, the central processorperforms steps 312 and 314. As disclosed in the '163 application, steps312 and 314 can comprise reference-signal processing, blind adaptivetechniques, directive, and/or retro-directive techniques. Communicationbetween the base transceiver stations and the at least one centralprocessor is provided by a high speed network backbone, or fronthaul,which may comprise optical fiber, wired connections, wirelessconnections, or any combination thereof. Pre-coded data is transmitted316 by multiple transmission points under the control of the centralprocessor. Each UE receives pre-coded transmissions from multipletransmission points and demodulates the received data 317.

In one aspect of the invention, joint transmissions by multiple cells(i.e., base transceiver stations) to a given UE employ the same time andfrequency radio resources. Dynamic cell selection provides for selectinga portion of the base station network to serve a particular UE.Furthermore, UE's can be selected for array processing, such as based ona UE's quality of service level. Pre-coding between the cells providesfor coherent transmission, which results in in-phase combining at thereceiver. With uplink multi-cell reception, the signal from a UE isreceived by multiple cells and combined. The UE does not need to beaware of whether multi-cell reception is occurring, so it should havelittle impact on the radio interface specifications.

As described in the '850 application, some aspects of the inventionprovide for sharing data and channel state information among groups ofbase stations to coordinate their transmissions in the downlink andjointly process the received signals in the uplink. These techniques caneffectively turn otherwise harmful inter-cell interference into usefulsignals, enabling significant power gain, increased channel rank, and/ordiversity advantages. While some systems disclosed herein describecellular base stations by way of example, it should be appreciated thatadditional and/or alternative radio transceivers may be employed,including fixed relay stations, remote radio heads, mobile stations,peer-to-peer radio transceivers, access points, and combinationsthereof.

FIGS. 4A and 4B are flow diagrams depicting spatial demultiplexingimplemented via multi-cell MIMO cooperation in wireless networks. Indense networks where interference emerges as the key capacity-limitingfactor, multi-cell cooperation can dramatically improve the systemperformance. Remarkably, such techniques can literally exploitinter-cell interference by allowing the user data to be jointlyprocessed by several interfering base stations, thus mimicking thebenefits of a large virtual MIMO array.

In FIG. 4A, UE's transmit reference signals 401 and data signals 403.Transmitted reference signals received by multiple base transceiverstations are measured to generate channel state information 402, fromwhich spatial demultiplexing weights are calculated 404. In one aspectof the invention, a central processor measures the channel stateinformation 402 and calculates demultiplexing weights 404 for ageographically distributed set of base transceiver stations. In anotheraspect of the invention, each base transceiver station measures thechannel state information 402, which is then forwarded to at least onecentral processor. In some aspects of the invention, distributedcomputing may be employed for calculating the spatial demultiplexingweights 404. For example, computational parts of step 404 may beperformed by multiple base transceiver stations. The central processorthen demultiplexes the data transmissions 406 received from the UEs.

In FIG. 4B, the transmission points and/or the central processor employblind-adaptive processing, such as disclosed in the '163 application, todemultiplex received data transmissions. Data signals transmitted 411 bythe UE are received and processed by multiple base transceiver stationsand at least one central processor. Blind adaptive processing provideschannel state information 412, which is used to calculate spatialdemultiplexing weights 414, which are used to demultiplex 416 the datatransmissions received from the UEs.

FIG. 5 is a flow diagram depicting a method in accordance with someaspects of the invention in which multiple transmission points and atleast one central processor cooperate to produce subspace pre-codeddownlink transmissions to multiple UEs. A base transceiver station(e.g., a transmission point) performs preliminary processing 501 ofsignals received from at least one UE and communicates channel stateinformation corresponding to each UE to at least one central processor503. The channel state information can include channel measurements madeby the UEs and/or the base transceiver stations. Thus, step 501 cancomprise measuring the channel(s) of each UE. The central processorcollects channel state information communicated by multiple basetransceiver stations 504, selects which base transceiver stations willserve each UE 506, calculates the distributed-antenna pre-coding 508,and coordinates the base transceiver stations to transmit pre-coded datasignals to the UEs 510. Each base transceiver station then transmitspre-coded data signals to the UEs 512.

A base transceiver station (or transmission point), as used throughoutthe disclosure, can comprise a NodeB (such as employed in a UTRANsystem) or an eNodeB (such as employed in an EUTRAN system). A centralprocessor, as used throughout the disclosure, can include a radionetwork controller (RNC) in a UTRAN system or an eNodeB in an EUTRANsystem. EUTRAN consists only of eNodeBs on the network side. The eNodeBperforms tasks similar to those performed by the NodeBs and RNC togetherin UTRAN.

E-UTRA uses OFDM-MIMO antenna technology depending on the terminalcategory and can use subspace pre-coding for the downlink to supportmore users, higher data rates, and lower processing power. In theuplink, LTE uses both OFDMA and Carrier Interferometry (also calledSingle-Carrier Frequency-Division Multiple Access), such as disclosedthroughout the '850 and '163 applications. This mitigates the very highpeak-to-average power ratio (PAPR) of conventional OFDM. For the uplink,in release 8 and 9, multi-user MIMO/Spatial division multiple access(SDMA) is supported.

LTE supports both Frequency-division duplex (FDD) and TDD modes. WhileFDD makes use of paired spectra for UL and DL transmission separated bya duplex frequency gap, TDD splits one frequency carrier intoalternating time periods for transmission from the base station to theterminal and vice-versa. Both modes have their own frame structurewithin LTE, and these are aligned with each other. Thus, similarhardware can be used in the base stations and user terminals.

FIG. 6 is a flow diagram depicting a method in accordance with someaspects of the invention in which multiple transmission points and atleast one central processor cooperate to perform distributed spatialdemultiplexing of uplink transmissions received from multiple UEs. Abase transceiver station (e.g., a transmission point) performspreliminary processing 601 of uplink signals received from at least oneUE and communicates channel state information corresponding to each UEto at least one central processor 603. The channel state information caninclude channel measurements made by the UEs and/or the base transceiverstations. Thus, in some aspects, step 601 can comprise measuring thechannel(s) of each UE. The central processor collects channel stateinformation communicated by multiple base transceiver stations 604,selects multiple base transceiver station antennas (including antennason different base stations) from which signals will be combined for eachUE 606, calculates the distributed-antenna demultiplexing weights 608,and performs spatial demultiplexing 610 to separate multiple same-bandsignals transmitted by the UEs and received by multiple base transceiverstations.

With respect to aspects of the disclosure, a multi-antenna wirelesscommunication system, such as one employing Coordinated Multipointtransmission and/or reception, can mitigate inter-cell interference. Insuch a system, multiple antennas are deployed across a plurality ofgeographically contiguous cells (or sub-cells) and connected to acentral processor, e.g., via a fast backhaul. This architecture enablesthe central processor to jointly process downlink signals transmittedfrom and/or uplink signals received at the multiple antennas, in orderto mitigate inter-cell interference.

In accordance with some aspects of the disclosure, to jointly processdownlink signals transmitted from the multiple antennas, in particular,the central processor is provided with information characterizing theassociated downlink channel responses. If the system employs FDD, theserved UEs measure these downlink channel responses and feed them backto the central processor. If the system instead employs TDD, thedownlink channel responses can advantageously be estimated from uplinksignals received at the multiple antennas based on the assumption thatfor TDD, the downlink channel can be inferred from the uplink channel(e.g., the uplink and downlink channels can be reciprocal).

This assumption of reciprocity between the downlink and uplink channel,however, may sometimes be inaccurate in a multi-antenna system. Forinstance, each of the multiple antennas is connected to a correspondingtransceiver that comprises a transmit-receive radio frequency (RF)chain. These transmit-receive RF chains may have different frequencyresponses, due for example to differences in the transfercharacteristics of the components (e.g., analog filters, poweramplifiers, etc.) making up those RF chains. If the RF chains of themultiple antennas do not have identical frequency responses, theassumption of reciprocity no longer proves accurate, which in turn canprevent advantageous estimation of the downlink channel responses fromuplink signals. Accordingly, the RF chains can be initially, and perhapsperiodically, calibrated with one another to account for differences intheir frequency responses, such as disclosed in U.S. Pat. No. 6,211,671,which is incorporated by reference in its entirety.

FIG. 7 is a flow diagram depicting messages passed between networkdevices corresponding to steps in a super-array processing method. Suchflow diagrams can assist a software developer in designing softwaremodules with instructions on non-transient computer-readable memory thatprogram a computer processor to perform methods disclosed herein.

In one aspect of the invention, a reference signal is transmitted 751,from which channel state information is calculated. For example, eachantenna on each of a plurality of base stations 701 and 702 can transmita reference signal (711 and 712, respectively), such as a known trainingsignal or a pilot tone, which a UE 700 receives and processes todetermine its channel state information.

In a feedback step 752, the UE transmits its channel state information713 and 714 back to its respective base station 701 and 702. The basestations 701 and 702 relay the channel state information (e.g., messages715 and 716) received from their UEs to at least one central processor710.

As should be appreciated from the disclosure, an alternative step 751can comprise the base stations 701 and 702 receiving transmittedreference signals from the UEs (such as UE 700) and estimating thechannels therefrom. Then the feedback step 752 comprises the basestations 701 and 702 relaying the channel state information 715 and 716to the at least one central processor 710.

In step 753, the central processor 710 calculates distributed antennasystem weights w₁ and w₂ 753 based on the channel state information 715and 716. In a cooperative-MIMO demultiplexing step (not shown), theweights can be used to demultiplex interfering data streams (not shown)in the uplink channels between the UEs 700 and base stations 701 and 702routed to the central processor 710.

Cooperative-MIMO multiplexing provides for employing the distributedantenna system weights for pre-coding data D to be transmitted to eachUE 700. For example, weight vectors w₁ and w₂ are used to pre-code adata matrix, and the pre-coded data signals 717 and 718 are routed totheir respective base stations 701 and 702. The base stations 701 and702 transmit signals 719 and 720 comprising the pre-coded data to theUEs 700.

As illustrated in FIG. 8, software developed in accordance with aspectsof the invention may comprise functionality that is separable intomultiple independent and interchangeable modules. In some aspects, amodule may comprise a software object. In some applications, a modulemay comprise a container that contains other objects. While the scale ofa module may vary depending on the programming language and theapplication, modules are typically designed to perform logicallydiscrete functions and interact via well-defined interfaces. It shouldbe appreciated that in some aspects of the disclosure, modules cancomprise data objects, and such data objects reside in physical memoryof a computing device and can comprise executable instructions stored inmemory that cause a processor to execute steps that give rise to thedisclosed functionality as described below.

FIG. 8 comprises pseudo-code that depicts data structures and processingfunctions that can be implemented by a computer processor programmed toperform methods in accordance with aspects of the invention, includingmethods disclosed in the '850 application. An object, such as a virtualarray object, V_array 840, can comprise methods and data structures thatpackage distributed-array assets (e.g., antenna systems of differentbase transceivers, radio signal processors associated with those antennasystems, baseband signal processing systems in the base transceiversand/or in the central processor(s), and front-haul networks) in a mannerthat conceals certain details. For example, the V_array object 840 maycomprise a private section 850 in which a combination of data structuresand functions can only be accessed within the object 840. By way ofexample, objects Bts 851 and Fronthaul 852 are private members. Privatedata structures and functions can conceal implementation details of theobject's 840 interface (e.g., how Public functions are implemented andhow Public data structures are created).

The virtual antenna array object 840 includes an implementation, whichis typically expressed by one or more functions, such as functions862-866. The implementation contains the working code that correspondsto the elements declared in the interface, such as the Antenna object861. Functions 862-866 may call other functions which may be internaland/or external to the object 840. By way of example, functionf_select_ue( . . . ) 862 selects UEs based on some predetermined qualityfactor, such as disclosed in the '850 application. Functionf_select_antenna( . . . ) 863 selects antennas in the array to serve aparticular UE, such as disclosed in the '163 application. Functionf_csi( . . . ) measures channel state information for each antenna/UEcombination, such as disclosed in the '850 application. Function f_mux(. . . ) provides for spatial multiplexed transmission of pre-coded dataacross the array of antennas (which may reside on multiplegeographically distributed base stations), such as disclosed in the '850application. Function f_rx( . . . ) receives data from a predeterminedset of antennas residing on multiple geographically distributed basestations, such as disclosed in the '850 application.

In one aspect of the invention, each Antenna object 861 is associatedwith an antenna on a base transceiver station (indicated by the Btsobject 851), so the virtual antenna array can include antennasassociated with different base stations, such as disclosed in the '850application. The base transceiver stations can be connected to a centralprocessor via a fronthaul network, such as disclosed in the '850application. Thus, the virtual array object 840 can comprise one or moreFronthaul objects 852 associated with communications between the Antennaobjects 861.

In some aspects of the invention, the virtual antenna array object 840conceals information related to its antenna elements being distributedacross multiple base transceivers (and/or UEs). For example, in someaspects, the virtual antenna array object 840 conceals information aboutfront-haul networks communicatively coupling signals between the antennaelements and signal processors (such as baseband processors, includingMIMO processors). Thus, each virtual antenna array object 840 canconceal network communications within an object-oriented interface.

In accordance with some aspects of the invention, the virtual antennaarray object 840 is part of a distributed control environment thatprovides services, such as access, interaction, and control of basetransceiver antennas in a network of geographically distributed basetransceivers.

A module interface expresses the data and/or functional elements thatare provided and required by the module. For example, the virtualantenna array object 840 could receive as its input an elementindicating a particular UE. Thus, a virtual antenna array could becreated for each UE. The elements defined in the interface are usuallydetectable by other modules. In one aspect of the invention, qualityfactors and signal strength are some of the parameter by which physicalantennas distributed across multiple base transceivers can be selectedfor inclusion in the virtual antenna array object 840. In some aspects,a quality factor or signal strength comprises a measurement of a knowntraining signal. Elements may comprise various data structures, such aslists, arrays, queues, stacks, and other objects. Each data structurehas associated operations that may be performed on it and pre-conditionsand constraints on the effects of those operations.

Once a virtual array object 840 is created, it may be passed as anargument to another module, such as a multi-user MIMO object, Mu_mimo810. For example, function calls 801 and 802 access functional elements822 and 821, respectively, in the Mu_mimo object's 810 interface 820. Insome aspects, arguments in the function calls 801 and 802 can comprisefunction calls in the V_array object's 840 interface.

The f_precode( . . . ) function 821 employs channel state information(csi) to generate a set of antenna array weights (such as via a privatefunction, f_weight( . . . ) 831). The weights are used by function 821to pre-code a data set (tx_data) to produce pre-coded data(precoded_data). The pre-coded data can then be transmitted by thef_mux( . . . ) function 865 in the same virtual array object 840 used bythe f_precode function 821. Thus, in accordance with some aspects of theinvention, the f_precode function 821 can perform multi-user MIMOpre-coding for an array of geographically distributed antennas. Thef_demux( . . . ) function 822 processes channel state information (csi)and received data (rx_data) from the virtual antenna array 840 todemultiplex the received data.

In the uplink, MIMO receiver processing techniques can be used toefficiently exploit the spatial dimensionalities of the MIMO channel toincrease WWAN capacity. In aspects of the invention, from an algorithmicperspective, there is no discernible difference in processing aplurality of different transmissions from a single UE configured forMIMO versus processing one signal from each of a plurality of differentUEs configured only for Single Input, Multiple Output (SIMO). Similarly,in some aspects of the invention in which fronthaul latency is eithernegligible or compensated for, there is no algorithmic difference inMIMO receiver processing whether the receiving array comprises antennasemployed on multiple base transceiver stations or an antenna array on asingle base transceiver station. In the downlink, in some aspects of theinvention in which fronthaul latency is either negligible or compensatedfor, there is no algorithmic difference in MIMO transmitter processingwhether the transmitting array comprises antennas employed on multiplebase transceiver stations or an antenna array on a single basetransceiver station. For these reasons, at least some implementationdetails of the virtual array object 840 can be concealed from themulti-user MIMO object 810.

A MIMO system employs multiple (N_(T)) transmit antennas and multiple(N_(R)) receive antennas for data transmission. A MIMO channel formed bythe N_(T) transmit and N_(R) receive antennas may be decomposed intoN_(C) independent channels, wherein N_(C)≤min {N_(T), N_(R)}. Each ofthe N_(C) independent channels is also referred to as a spatialsubchannel (or subspace channel) and corresponds to a dimension. In onecommon MIMO system implementation, the N_(T) transmit antennas arelocated at and associated with a single transmitter system, and theN_(R) receive antennas are similarly located at and associated with asingle receiver system. A Cooperative-MIMO system can be effectivelyformed for a multiple access communication system having a set of basetransceiver stations communicatively coupled together and coordinated toconcurrently communicate with a number of UEs. In this case, each basetransceiver station and each terminal can be equipped with one or moreantennas. A Cooperative-MIMO system can be effectively formed for amultiple access communication system having a multiple UEscommunicatively coupled together and coordinated to concurrentlycommunicate with at least one base transceiver station. In this case,the base transceiver station is typically equipped with multipleantennas and each terminal can be equipped with one or more antennas.However, if geographically distributed base transceiver stations areemployed, each base transceiver station can be equipped with one or moreantennas.

The wireless links between the distributed base transceiver stationantennas and the UE antennas are modeled as a complex channel matrix Hof dimensions K×N_(T), where K is the aggregate number of UE antennasand N_(T) is the number of distributed antennas. H_(DL) is the DLchannel matrix and H_(UL) is the UL channel matrix. Channel reciprocityholds if DL and UL are set to the same carrier frequency:H _(DL) =H _(UL) ^(T) =Hwhere the superscript symbol, “^(T)”, denotes the transpose matrixoperation.

In one aspect of the invention, channel estimation is initiated withtransmission of a training signal by each of the antennas of a pluralityN of base stations. Assuming M antennas per base station, there areN_(M) training signal transmissions.

Each UE receives each training signal through each of its antenna(s) andfrequency down-converts the training signal to baseband, where it isdigitized and processed. Signal characterization logic, such asrepresented by function f_csi( . . . ) 864 characterizes the channelfrom the received training signal (e.g., identifying phase and amplitudedistortions, such as in the case of a flat fading channel, orcalculating a channel impulse response) and stores the characterizationin memory. Some aspects of this characterization process are similar tothat of prior-art MIMO systems, with a notable difference being that theeach UE only computes the characterization vector for its own antenna(s)rather than for all K antennas, and each UE is configured to performchannel characterization from training signals transmitted from multiplebase transceiver stations. In other aspects of the invention, functionf_csi( . . . ) 864 characterizes the channel from training signalstransmitted by the UEs. Thus, function f_csi( . . . ) 864 may reside onthe base transceiver stations and/or the central processor. Inaccordance with some aspects of the invention, software objects, andeven components with software objects disclosed herein may reside onmultiple devices, including UEs, base transceiver stations, and centralprocessors.

In accordance with one aspect of the invention, each UE produces asub-matrix of a full cooperative-MIMO channel matrix H. For example, ifa UE has one antenna (or it has multiple antennas and a combining systemthat combines signals received by the multiple antennas), then a channelestimate corresponding to a training signal transmitted by one antennaof one of the base stations is an element of a 1×N_(T) vector, whereN_(T) is the total number of base station antennas, expressed by

${N_{T} = {\sum\limits_{n = 1}^{N}\; M_{n}}},$where N is the number of base stations, and M_(n) is the number ofantennas corresponding to an n^(th) base station. In some aspects, achannel estimate comprises a complex-valued flat-fading coefficient. Insome aspects, a channel estimate comprises a matrix, such as an impulseresponse vector.

In accordance with an aspect of the invention, a first UE having asingle antenna generates a 1×N_(T) vector of channel characterizationdata: [H_(1,1), H_(1,2), . . . H_(1,N) _(T) ]. A second UE having asingle antenna generates a 1×N_(T) vector of channel characterizationdata: [H_(2,1), H_(2,2), . . . H_(2,N) _(T) ]. A k^(th) UE having asingle antenna generates a 1×N_(T) vector of channel characterizationdata: [H_(k,1), H_(k,2), . . . , H_(k,N) _(T) ]. This channelcharacterization data can be a data set (e.g., csi) within the V_arrayobject 840.

Based on channel conditions and/or proximity of a UE to each basestation, a particular set of base stations may be selected to serve theUE. For example, this selection process may be performed by thef_select_antenna( . . . ) function 863. Thus, one or more UEs may beassigned to a subset of the total number of base stations. In suchinstances, values of the channel characterization data corresponding toa non-serving base station relative to a UE may equal zero. In somecases, certain values of the full cooperative-MIMO channel matrix H,such as matrix elements corresponding to indices of non-serving basestation antennas relative for a particular UE, may be set to zero

In some aspects of the invention, a k^(th) UE comprises multiple N_(k)antennas configured to perform MIMO. For each UE's antenna, a channelestimate corresponding to a training signal transmitted by one antennaof one of the base stations is an element of a 1×N_(T) vector. Thus, thek^(th) UE can generate an N_(k)×N_(T) submatrix of the fullcooperative-MIMO channel matrix H.

The UEs upload their channel characterization sub-matrices to the basestations via the WWAN, and the sub-matrices are communicated to thecentral processor via the fronthaul network. Thus, in some aspects, thef_csi( . . . ) function 864 can comprise components distributed acrossUEs, base stations, and one or more central processors. As the centralprocessor collects the channel characterization sub-matrices, they arestored as the full K×N_(T) cooperative-MIMO channel matrix H., where Kis the total number of UE antennas and N_(T) is the total number of basestation antennas.

Since each UE is an independent device, each UE often receives its ownunique data stream. Thus, in some aspects of the invention, the centralprocessor sources multiple data streams and routes them as separate datastreams intended for each UE. In order to do this, the central processorcomprises precoding logic for precoding the signals transmitted fromeach antenna of each of the base stations based on the signalcharacterization matrix H. In one aspect of the invention, thepre-coding logic is implemented via one or more software instructions,such as the f_precode( . . . ) function 821 in the Mu_mimo object 810.The central processor then routes the precoded data (or the precodingweights and data symbols) to the plurality of base stations. Routing canbe part of the f_precode( . . . ) function 821, or it can comprise aseparate function call. Thus, each base station antenna is configured totransmit a subspace-coded data sequence which is a function of the datasymbols and the channel matrix H.

In one aspect of the invention, cooperative MIMO improves the uplinkcommunications (i.e., the link from the UEs to the Base Stations). Inthis aspect, the channel from each UE is continually analyzed andcharacterized by uplink channel characterization logic residing in eachbase transceiver station or central processor, which may be implementedby the f_csi( . . . ) function 864. For example, each UE may transmit atraining signal, which the channel characterization logic analyzes(e.g., as in a typical MIMO system) to generate the channelcharacterization matrix H.

As described throughout the '163 application, the '854 application, andthe '107 application, all of which are incorporated by reference intheir entireties, various spatial processing techniques may be employed.Such processing techniques may be included within the f_precode 821 andf_demux 822 functions.

In one aspect of the invention, f_demux 822 performs linear spatialprocessing on the received signals (for a non-dispersive MIMO channelwith flat fading) or space-time processing on the received signals (fora dispersive MIMO channel with frequency selective fading). The spatialprocessing may be achieved using linear spatial processing techniquessuch as a channel correlation matrix inversion technique, a minimum meansquare error (MMSE) technique, and others. These techniques may be usedto null out the undesired signals and/or to maximize the received SNR ofeach of the constituent signals in the presence of noise andinterference from the other signals. The space-time processing may beachieved using space-time processing techniques such as an MMSE linearequalizer, a decision feedback equalizer (DFE), a maximum-likelihoodsequence estimator (MLSE), and others. In some aspects, iterativecancellation techniques, such as successive interference cancellationmay be employed.

In some aspects of the invention, f_precode 821 performs directiveand/or retro-directive techniques for calculating antenna array weightsfor transmission in a distributed antenna system. Such techniques aredisclosed in the '163 application. In some aspects of the invention, asdisclosed in the '187 application, eigenvalue-decomposition approaches,such as singular value decomposition, may be employed for transmitterspatial processing.

For example, a MIMO channel formed by the N_(T) transmit antennascomprising multiple transmission nodes (e.g., base stations) and N_(R)receive antennas comprising multiple UEs can be characterized by anN_(R)×N_(T) channel response matrix H for each OFDM subband, whereineach matrix element h_(i,j) of H denotes coupling or complex channelgain between transmit antenna j and receive antenna i. For simplicity,the MIMO channel is assumed to be full rank with S=N_(T)≤N_(R).

For data transmission with eigensteering, eigenvalue decomposition canbe performed on a correlation matrix of H to obtain S eigenmodes of H,as follows:R=H ^(H) ·H=E·A·E ^(H),where R is a correlation matrix of H; E is a unitary matrix whosecolumns are eigenvectors of R; A is a diagonal matrix of eigenvalues ofR; and “^(H)” denotes a conjugate transpose.

A unitary matrix U is characterized by the property U^(H)U=I, where I isthe identity matrix. The columns of a unitary matrix are orthogonal toone another, and each column has unit power. The matrix E is also calledan “eigenmode” matrix or a “transmit” matrix and may be used for spatialprocessing by the central processor to transmit data on the S eigenmodesof H. The eigenmodes may be viewed as orthogonal spatial channelsobtained through decomposition. The diagonal entries of A areeigenvalues of R, which represent the power gains for the S eigenmodes.The eigenvalues in A may be ordered from largest to smallest, and thecolumns of E may be ordered correspondingly. Singular valuedecomposition may also be performed to obtain matrices of left and righteigenvectors, which may be used for eigensteering.

For data transmission with eigensteering, the transmitting entity mayperform spatial processing for each subband as follows:z=E·s,where s is a vector with up to S data symbols to be sent on a particularsubband; and z is a vector with N_(T) spatially processed symbols forthe subband. In general, D data symbols may be sent simultaneously on D(best) eigenmodes of H for each subband, where 1≤D≤S. The D data symbolsin s are spatially processed with D columns of E corresponding to the Dselected eigenmodes.

For data transmission with a spatial spreading matrix, such as a CIspatial spreading matrix, the transmitting entity may perform spatialprocessing for each subband as follows:z _(ss) =V·swhere V is a spatial spreading matrix for the subband; and z_(ss) is avector with up to N_(T) spread symbols for the subband. Each data symbolin s is multiplied with a respective column of V to obtain up to N_(T)spread symbols.

In general, D data symbols may be sent simultaneously on each subbandwith matrix spreading, where 1≤D≤S. The D data symbols in s may bemultiplied with a N_(T)×D spreading matrix V(k) to obtain N_(T)spatially processed symbols for z_(ss). Each spatially processed symbolfor each subband includes a component of each of the D data symbolsbeing sent on the subband. The N_(T) spatially processed symbols foreach subband are then transmitted on the S spatial channels of H.

As disclosed throughout the '187 application, any of variouswater-filling or water-pouring schemes may be employed to optimallydistribute the total transmission power over the available transmissionchannels, such as to maximize spectral efficiency. For example,water-filling can be used to adapt individual UE transmission powerssuch that channels with higher SNRs are provided with correspondinglygreater portions of the total transmit power. A transmission channel, asdefined herein, may include a spatial (e.g., a sub-space) channel, aspace-frequency channel, or some other channel defined by a set oforthogonalizing properties. Similarly, water filling may be used at aphysically connected (i.e., wired) antenna array. The transmit powerallocated to a particular transmission channel is typically determinedby some predetermined channel-quality measurement, such as SNR, SINR,BER, packet error rate, frame error rate, probability of error, etc.However, different or additional criteria may be employed with respectto power allocation, including, but not limited to, UE battery life,load balancing, spatial reuse, power-control instructions, and near-farinterference.

The modulation and channel coding for each transmission channel may beadapted with respect to the corresponding SNR. Alternatively,transmission channels may be grouped with respect to their data-carryingcapability. Thus, groups of transmission channels may share commonmodulation/coding characteristics. Furthermore, transmission channelshaving particular SNRs may be used for particular communication needs.For example, voice communications may be allocated to channels havinglow SNRs, and thus, data-carrying capabilities. In some cases,transmission channels that fail to achieve a predetermined threshold SNRmay be eliminated. In one embodiment of the invention, water filling isemployed such that the total transmission power is distributed overselected transmission channels such that the received SNR isapproximately equal for all of the selected channels.

In accordance with some aspects of the invention, hardware systems, suchas UEs, base transceiver stations, and central processors, can include aprocessing element capable of executing processing threads or tasks.

As depicted in FIG. 9, a UE can include a controller, such as at leastone computer or data processor 910, at least one non-transitorycomputer-readable memory medium embodied as a memory 920 that stores aprogram of computer instructions 921, and at least one suitable radiofrequency (RF) transmitter/receiver 901 for bidirectional wirelesscommunications with multiple base transceiver stations via one or moreantennas 905.

As depicted in FIG. 10, a base transceiver station includes acontroller, such as at least one computer or a data processor 1012, atleast one computer-readable memory medium embodied as a memory 1014 thatstores a program of computer instructions 1016, and at least onesuitable transceiver 1002 for communication with the UEs via one or moreantennas 1001.1-1001.N_(M). The base transceiver station is coupled viaa fronthaul transceiver 1020 to a data and control path to the centralprocessor, such as a network control element. In one aspect of theinvention, the fronthaul may be implemented as an Si interface. Inanother aspect, the fronthaul may comprise an X2 interface. In anotheraspect, the fronthaul can comprise a direct eNodeB internal interface(e.g., optical fiber connection)) such as a connection between a radioremote head and an eNodeB.

Thus, there is some central unit where several base transceiver stationsare connected as such, with the goal being that the base transceiverstations (e.g., transmission points, macro eNodeBs, etc.) are centrallycontrolled together. The control can be at the location of a macroeNodeB, but could also be at a different location.

As depicted in FIG. 11A, a central processor, such as a network controlelement, comprises a controller, such as at least one computer or a dataprocessor 1112, at least one computer-readable memory medium embodied asa memory 1114 that stores a program of computer instructions 1116, andat least one fronthaul transceiver 1120 coupled to a data and controlpath (i.e., a fronthaul network) between the central processor andmultiple base transceiver stations.

At least one of the programs 921, 1016, and 1116 is assumed to includeprogram instructions that, when executed by the associated computerprocessor(s), enable the corresponding device(s) to operate inaccordance with the exemplary aspects of the invention.

The '163 application discloses SDR platforms that enable dynamicimplementations of a full protocol stack, including Physical-layerprocessing. Some aspects are disclosed in the context ofsoftware-defined networks, such as to enable more dynamic organizationof resources. Disclosed software radio implementations includeinstantiations of virtual base stations.

In some disclosed aspects, software radio provides associated controloperations, such as identifying a particular transmission protocol usedby a particular device, reserving channels for transmission, monitoringchannel use (including channel reservation and channel release),requesting data transmissions and/or state information from remotedevices, attaching tags to data streams for identification and/or accesscontrol, and providing instructions to remote transceivers to adjust orcontrol processing, transmit status information, and/or identification.

By way of example, and with respect to implementing base transceiverstation processing in a central processor or in a distributed computingsystem, a software-defined radio in accordance with one aspect of theinvention can provide a base station instantiation for a UE.Specifically, the software-defined radio can perform base stationprocessing functionality in combination with Cooperative-MIMO subspaceprocessing to use a plurality of geographically distributed basetransceiver stations that communicate with the UE via the radio accessnetwork. In an LTE network, this means that the software-defined radioimplements a virtual eNodeB to support the LTE protocol stack for thatuser while providing for subspace coding to support spatialmultiplexing.

In one aspect, when a UE joins the network, the SDR might provide forrequesting identification, performing channel reservation, andrequesting state information (e.g., channel state information) from theUE. The combination of software-defined radio and Cooperative-MIMOimplemented with virtualized base station processing via the centralprocessor or even distributed (e.g., cloud) computing enables each UE tobe served independently of other UEs concurrently employing the samespectrum, and possibly using the same base transceiver station hardware.This is because Cooperative-MIMO subspace processing enables multiplenon-interfering subspace channels in the same spectrum to be used byeach UE, even closely spaced UEs, which can eliminate the need for othermultiple access partitioning of the spectral resource (such as via TDMA,OFDMA, CDMA, etc.). When the UE ends its connection with the network,the SDR releases the channel and its instantiated virtual base station.

In accordance with some aspects, consolidation of processing frommultiple base stations to a central processor (e.g., an offsite datacenter) constitutes a virtual base station that employs multipleantennas of different base transceiver stations and remote (and possiblysoftware-defined) base station processing. Further aspects distributethe base station processing over multiple processing cores viadistributed (e.g., cloud) computing. As disclosed in the '163application, multiple different transmission protocols may be employedsimultaneously. Thus, SDR instances (e.g., virtual base stations)employing different protocol stacks may coexist within the samesoftware-defined radio and can be implemented concurrently within thesame spectrum.

A CI-based software radio can extend adaptive link-layer techniques tothe physical layer. This enables more efficient use of the spectrum bydynamically adjusting physical-layer characteristics to current channelconditions, network traffic, and application requirements. CI cansignificantly improve wireless network performance and functionality byadapting to different requirements for bandwidth, error rate, latency,link priority, and security.

Embodiments of a CI-based communication system may include interactivecapabilities between the physical layer and higher layers such that aresponse to changing conditions and operational requirements can bedirected to an appropriate physical-layer function. For example, a basestation or central processor in a mobile wireless network candynamically create channels (e.g., spatial multiplexing channels)depending on the number of mobile units in its coverage area and theirservice requirements. When additional units enter the area, the systemcan be reconfigured accordingly.

In ad-hoc networks, base station functions (e.g., routing, powercontrol, synchronization, geo-location services, etc.) may bedistributed among various devices. Aspects of the disclosure can alsoinclude adapting base-station and access-point functions to maintainlink quality and perform load balancing (including managing powerbudgets for devices acting as routers and relays, managing systemspectrum allocations, and/or adjusting cell boundaries to adapt tochanging user demands, power budgets, and spectrum use). Thus, in someaspects, the super-array processing system 112 may include a powercontrol 114.3.

Bandwidth can be dynamically allocated to uplink and downlink channelsdepending on network traffic characteristics. Units requiring real-timeor broadband services may be assigned to dedicated channels, whereasunits having bursty data requirements may be assigned to a sharedchannel. Aspects of the invention can provide for combinations oftime-domain and frequency-domain processing to produce signals havingdesired physical-layer characteristics.

SDRs disclosed in the '163 application are configured to provide forvarious signal processing objectives for implementing multiple-accessprotocols (e.g., DS-CDMA, TDMA, OFDM, MC-CDMA), channel coding,modulation (e.g., phase modulation, frequency modulation, amplitudemodulation, time-offset modulation, etc., including differentconstellations (e.g., binary, M-ary), multiplexing (e.g., TDM, FDM,CDM), formatting (e.g., frame length, headers, payload length, etc.),source coding, providing for frequency agility (e.g., frequency hopping,variable aggregate bandwidth, frequency selectability, etc.),encryption, and/or sub-channel coding.

FIG. 11B is a block diagram that depicts a cloud-based software-definedradio, such as disclosed in the '163 application. A plurality ofhardware components (such as servers 1101 and 1102) are communicativelycoupled together via a network 1190. Server 1101 comprises at least oneprocessor (e.g., CPU 1161) and at least one memory 1141. Similarly,server 1102 comprises at least one processor (e.g., CPU 1162) and atleast one memory 1142. A software-defined radio platform can comprise aplurality of signal-processing software components residing in one ormore of the memories 1141 and 1142 of the hardware components, 1101 and1102, respectively. By way of example, SDRs 1151.1-1151.i are stored inmemory 1141, and SDRs 1152.1-1152.j are stored in memory 1142. By way ofexample, the hardware components 1101 and 1102 may include a computermain frame or a workstation.

Although not shown, interfaces can couple the hardware components 1101and 1102 together, such as via the network 1190. Such interfacesdisclosed in the '163 application include radio interfaces for a radionetwork. The network 1190 may comprise various types of networks,including a bus. Also disclosed in the '163 application is the conceptof interfaces for the software components (e.g., 1151.1-1151.i and1152.1-1152.j) as it relates to software design, such as object orienteddesign. Interaction and inter-connectivity between software and hardwareinterfaces is also contemplated for coupling together hardware and/orsoftware components.

The SDRs 1151.1-1151.i and 1152.1-1152.j may include local and/or remotecomputer programs configured to process signals, such as for variousphysical-layer signal processing, including baseband processing. Forexample, the SDRs 1151.1-1151.i and 1152.1-1152.j may include one ormore programs for performing digital signal processing. One or more ofthe SDRs 1151.1-1151.i and 1152.1-1152.j may provide control signals toone or more hardware components such as to select, adapt, or otherwisereconfigure signal processing.

The memory can comprise various types of storage mediums (e.g., diskdrive, tape drive, CR Rom, DVD, flash memory, or any other storagedevice) for storing application programs (e.g., the SDRs 1151.1-1151.iand 1152.1-1152.j) and data. Hardware and/or the software may performA/D conversion, as necessary. In some applications, modulation and/ordemodulation may be performed digitally with any combination of softwareand hardware.

In one set of aspects of the invention, a software component (such as atleast one of the SDRs 1151.1-1151.i and 1152.1-1152.j) residing at aremote receiver location (e.g., a base transceiver station) receivessignals transmitted in the radio access network, processes the receivedsignals, and conveys some control information in the data stream (e.g.,in a header or pilot channel) to hardware components residing in anotherlocation (e.g., at a central processor or another base transceiverstation). Signal-processing operations may be distributed throughout anetwork in a way that balances processing loads and/orcommunication-resource (e.g., spectrum use) loads. Alternatively, in aCooperative-MIMO network wherein UEs cooperate with a base transceiverstation to perform joint processing for spatial multiplexing and/ordemultiplexing signals, most of the signal processing may be performedby the base transceiver station (and/or the central processor) to reducethe cost and complexity (and power usage) of the UEs. As described withrespect to centralized processing of base transceiver operations, RFprocessing is performed at each base transceiver station, and most orall of the baseband signal processing may be performed at a centralprocessing facility.

In one set of aspects of the disclosure, software can be uploaded to aremote transceiver (e.g., base transceiver station) via one or morecommunication channels. This simplifies software updates and enhancessignal-processing versatility of the network. In another set of aspects,software updates can be uploaded to a central processor (e.g., a cloudnetwork organized by a central processor) where most or all of thebaseband processing is performed.

Software-based radios can provide adaptability to differentcommunication standards. The '163 application discloses various systemsand techniques that can migrate many different transmission protocols toa common high-performance SDR platform that is suitable for allapplications. In some aspects of the disclosure, the SDR platform can beconfigured to enable coexistence of different standard systems withinthe same spectrum. For example, the power emission, frequency band, orother configuration parameters of a legacy radio access network can beadjusted to accommodate the adoption of new transmission protocols whileavoiding harmful interference with the legacy protocol.

As new wireless standards are developed to enhance data rate andcoverage in the radio access network, the base transceiver stationsand/or central processors can be updated to support those standards. Insome aspects, only the central processor(s) needs to be updated. By wayof example, the central processor may comprise distributed computingresources, such as multiple servers residing in one or more datacenters. The servers may comprise hardware components of an SDRplatform.

In one aspect, the base transceiver stations and/or central processorsare SDRs equipped with programmable computational capability, such asFPGA, DSP, CPU, GPU, and/or GPGPU, configured to run algorithms forbaseband signal processing in the radio access network. If the standardis upgraded, new baseband algorithms can be uploaded to the centralprocessors and/or from the central processors to the base transceiverstations to reflect the new standard. This SDR feature allows forcontinuous upgrades to the radio access network, such as when newtechnologies are developed to improve overall system performance.

In one aspect of the disclosure, a cloud SDR network comprises amulti-user MIMO system implemented with cooperative-MIMO over aplurality of geographically distributed base transceiver stationscommunicatively coupled to a central processor. The central processor isconfigured to perform at least some of the baseband processing in theradio access network. In some aspects, the central processor and thebase transceiver stations are configured to exchange information toreconfigure system parameters, such as to dynamically adapt to changingconditions of the radio access network, including the networkarchitecture (such as described in the '187 application).

As disclosed with respect to coordinated multipoint systems with acentral processor configured to perform cooperative MIMO, the basetransceiver stations in a cloud SDR network can be configured togenerate simultaneous non-interfering wireless links to serve differentUEs with different multiple access techniques (e.g., TDMA, FDMA, CDMA,OFDMA, etc.) and/or different modulation/coding schemes. For example, ifthe base transceiver stations perform RF processing and the centralprocessor performs just baseband processing, the SDRs can be configuredto perform baseband processing. Based on the active UEs in the radioaccess network and the standard(s) they use for their wireless links,the SDRs implemented by the central processor (such as SDRs in adistributed computing environment) can instantiate virtual base stationprocesses in software, each process configured to perform the basebandprocessing that supports the standard(s) of its associated UE(s) whileutilizing a set of the base transceiver stations within range of theUE(s).

In accordance with one aspect of the invention, baseband waveforms frommultiple ones of the SDRs 1151.1-1151.i and 1152.1-1152.j are coupledinto the Super-Array Processing System 112 depicted in FIG. 2. Thebaseband waveforms are combined in the SpatialMultiplexing/Demultiplexing module 114.1 using Cooperative-MIMO subspaceprocessing to produce multiple pre-coded waveforms. The routing module114.2 sends the pre-coded waveforms over the fronthaul 105 to multipleones of the base transceiver stations' 101.1-101.N antennas102.1-102.M₁, 106.1-106.M₂, and 104.1-104.M_(N). The base transceiverstations 101.1-101.N can be coordinated to concurrently transmit thepre-coded waveforms such that the transmitted waveforms propagatethrough the environment and constructively interfere with each other atthe exact location of each UE 120.1-120.K. The coherent combining ofthese waveforms at the location of each UE 120.1-120.K results in thesynthesis of the baseband waveform that had been output by the SDRinstance 1151.1-1151.i and 1152.1-1152.j associated with that UE120.1-120.K. Thus, all of the UEs 120.1-120.K receive their ownrespective waveforms within their own synthesized coherence zoneconcurrently and in the same spectrum.

In accordance with one aspect of the invention, each UE's correspondingsynthesized coherence zone comprises a volume that is approximately acarrier wavelength or less in width and centered at or near each antennaon the UE. This can enable frequency reuse between nearby—evenco-located—UEs. As disclosed in the '107 application, the SpatialMultiplexing/Demultiplexing module 114.1 can be configured to performmaximum ratio combining. Any of various algorithms for MIMO processingdisclosed in the '107 application may be employed by methods andapparatus aspects disclosed herein. In some aspects, the module 114.1can perform zero forcing, such as to produce one or more interferencenulls, such as to reduce interference from transmissions at a UE that isnot an intended recipient of the transmission. By way of example, butwithout limitation, zero forcing may be performed when there are a smallnumber of actual transmitters (e.g., base transceiver station antennas)and/or effective transmitter sources (e.g., scatterers in thepropagation environment).

By way of example, FIG. 12 is a block diagram that depicts a centralprocessor 1100 communicatively coupled via a fronthaul network 1240 tomultiple base transceiver stations, such as base transceiver stations1271 and 1272. Each base transceiver station 1271 and 1272 comprises aWWAN transceiver 1202 and 1203, respectively, and baseband processor1212 and 1213, respectively. WWAN transceiver 1202 comprises a number Niof WWAN transceiver antennas 1204.1-1204.N₁, and WWAN transceiver 1204comprises a number N_(M) of WWAN transceiver antennas 1205.1-1205.N_(M).The baseband processor 1212 comprises a computer processor 1214 and amemory 1216. The baseband processor 1213 comprises a computer processor1215 and a memory 1217. In accordance with some aspects of thedisclosure, the baseband processors 1212 and 121 comprise Channel StateInformation processing logic 1218 and 1219, respectively, and ChannelState Information routing logic 1220 and 1221, respectively. Each basetransceiver station 1271 and 1272 comprises a fronthaul transceiver 1230and 1231, respectively, communicatively coupled via the fronthaulnetwork to the central processor 1100.

In accordance with some aspects of the disclosure, Channel StateInformation processing logic 1218 and 1219 can collect channelinformation uploaded by the UEs (not shown) and/or determine channelstate information from measurements of training signals transmitted bythe UEs (not shown). Channel State Information routing logic 1220 and1221 can route channel state information to at least one centralprocessor, such as the central processor 1100.

In some aspects of the disclosure, the central processor 1100 comprisesChannel State Information processing logic 1126, Pre-coding logic 1136,and Base Station Routing logic 1146. In one aspect, computer software,such as logic 1126, 1136, and 1146, comprises instructions stored on anon-transitory computer-readable medium (e.g., memory 1114), that whenexecuted on the processor 1112, perform the steps of storing the WWANchannel state information received from the base transceiver stations(e.g., base transceiver stations 1271 and 1272) based on the WWANchannel state information and/or at least one quality metric thatcharacterizes each communication link between a base transceiver stationand a UE; and selecting a plurality of antennas residing on multiplebase transceiver stations to provide a set of distributed antennas. Forexample, a set of distributed antennas can be selected to serve each UE.Next, the processor 1112 calculates subspace processing weights fromeach UE's channel state information for the each UE's corresponding setof distributed antennas. The corresponding instructions can be in thePre-coding logic 1136 and/or in subspace demultiplexing logic (notshown). The processor 1112 coordinates each UE's corresponding set ofdistributed antennas to communicate in the WWAN via the fronthaulnetwork. For example, the corresponding instructions for coordinatingthe distributed antennas can be in the Base Station Routing logic 1146.The central processor 1100 provides for performing at least one ofsubspace multiplexing of WWAN signals transmitted by each set ofdistributed antennas and subspace demultiplexing signals received byeach set of distributed antennas.

The exemplary aspects of the disclosure may be implemented, at least inpart, by computer software executable by the data processor 910 of theUEs (such as the UE shown in FIG. 9), the data processor 1012 of thebase transceiver stations (such as the base transceiver station shown inFIG. 10), by the data processor 1112 of the central processor (such asthe central processor shown in FIG. 11A), by multiple data processors ina distributed computing system (not shown), and/or by hardware, or by acombination of software, hardware, and firmware.

In accordance with one aspect of the invention, subspace multiplexing isprovided by the Pre-coding logic 1136 configured to produce pre-codedsubspace (i.e., spatial multiplexing) weights and to encode data withthe weights, and the Base Station Routing logic 1146 configured to routethe encoded data to the base transceiver stations for transmission tothe UEs. In accordance with another aspect of the invention, subspacedemultiplexing is provided by the Base Station Routing logic 1146configured to route UE uplink signals received by the base transceiverstations to the central processor 1100 and the subspace demultiplexinglogic (not shown) configured to produce subspace demultiplexing weightsbased on the channel state information and to de-multiplex (i.e.,decode) the received signals. Thus, performing at least one of subspacemultiplexing of WWAN signals transmitted by each set of distributedantennas and subspace demultiplexing signals received by each set ofdistributed antennas enables multiple UEs to employ simultaneousinterference-free same-band communications.

In accordance with some aspects of the invention, certain features, suchas pre-coding logic and subspace demultiplexing logic, can comprise anApplication Programming Interface (API) or library that definesfunctionalities that are independent of their respectiveimplementations, which allows definitions and implementations to varywithout compromising each other. By way of example, and withoutlimitation, APIs provided for base station network control can enableMIMO processing applications to operate on an abstraction of thenetwork, such as by exploiting distributed antenna array systems andcoordinated base station operations and capabilities, without being tiedto the details of their implementation.

In accordance with some aspects of the disclosure, the steps ofselecting antennas on multiple base transceiver stations for MIMOprocessing and coordinating the multiple base transceiver stations forcooperative-MIMO communications (which includes routing communicationsignals to and/or from the multiple base transceiver stations as part ofa cooperative subspace processing operation) tie the mathematicaloperation (i.e., multi-user MIMO subspace processing) to specific andmeasurable operational benefits (i.e., based on measurable physicalphenomena), such as the ability to improve WWAN performance (e.g.,spectral efficiency, number of subspace channels, data rate per user,number of users supported, SNR, BER, etc.).

These steps add significantly more to MIMO processing than mere computerimplementation. By employing steps, such as selecting multiple basetransceiver stations to simultaneously serve each UE in a MIMO subspaceprocessing operation, coordinating the selected multiple basetransceiver stations to perform in a subspace multiplexing and/ordemultiplexing process, and provisioning at least one central processorto perform subspace multiplexing and/or demultiplexing of signalstransmitted by and/or received from the selected multiple basetransceiver stations, the corresponding aspects of the invention gobeyond the mere concept of simply retrieving and combining data using acomputer.

In accordance with the disclosure, the various data processors,memories, programs, transceivers, and interfaces, such as depicted inFIGS. 9, 10, 11, and 12, can all be considered to represent means forperforming operations and functions that implement the disclosednon-limiting aspects and embodiments.

The computer-readable memories (e.g., memories 920, 1014, 1114, 1216,and 1217) may be of any type suitable to the local technical environmentand may be implemented using any suitable data storage technology, suchas semiconductor based memory devices, random access memory, read onlymemory, programmable read only memory, flash memory, magnetic memorydevices and systems, optical memory devices and systems, fixed memoryand removable memory. The computer processors (e.g., computer processors910, 1012, 1112, 1214, and 1215) may be of any type suitable to thelocal technical environment, and may include one or more of generalpurpose computers, special purpose computers, microprocessors, digitalsignal processors (DSPs) and processors based on multi-core processorarchitectures, as non-limiting examples.

In accordance with aspects of the invention depicted and described inthe '163 application, FIG. 13A illustrates a subspace processing methodconfigured in accordance with some aspects of the invention. Adata-sequence vector u having length N is provided to a transmit filter1301 before being coupled into a communication channel 99. The channel99 acts on a transmitted data vector x via an N×N non-singular matrix Hand an additive noise vector n having a variance of N_(o)/2. A signalvector y received from the channel 99 is expressed by:y=Hx+n

The received signal vector y is processed by a matched filter 1302 togenerate an output signal vector z, which is expressed by:z=R _(f) x+n′where R_(f)=H*H and n′=H*n. An estimate of x given z is expressed by:{tilde over (x)}=R _(b) z+ewhere R_(b) ⁻¹=R_(f) (N_(o)/2)R_(xx) ⁻¹, R_(xx) is the covariance of x,and e is the MMSE error. Additional processing, such as any of variousadaptive feedback techniques, may be incorporated at the receiver end.

Although sub-space processing is commonly associated with arrayprocessing, the '163 application also discloses coding and decodingbased on sub-space processing techniques. For example, as a signal isrouted from one node to at least one other node in a network,algebraically unique linear codes are applied to the data for each“hop.” In one set of embodiments, sub-space processing and CI methodscan be combined. Sub-space processing can include frequency-diversityinterferometry and/or interferometry between one or more sets ofdiversity-parameter values including, but not limited to, polarizations,codes, modes, phases, and delays.

As disclosed in the '163 application, FIG. 13B illustrates a subspaceprocessing method that employs decision feedback. In this case, Choleskyfactorization provides:R _(f) =G*S _(o) Gwhere S_(o) is a diagonal matrix and G is a monic, upper-diagonalmatrix. A decision feedback equalizer includes a feed-forward filter1303, a decision system 1304, and a feedback filter 1305. An exemplarydecision feedback equalization algorithm is represented by:{tilde over (z)}=S _(o) ⁻¹ G ⁻ *H*y

-   -   for k=0, N−1

${\hat{x}}_{N - k}:={{decision}\left( {{\overset{\sim}{z}}_{N - k} - {\sum\limits_{i = 1}^{k}\;{g_{{N - k},{N - k + i}}{\hat{x}}_{N - k + i}}}} \right)}$

-   -   end        where g_(ij) are elements of G, and {circumflex over (x)}_(i)        and {circumflex over (z)}_(i) are elements of {circumflex over        (x)} and {circumflex over (z)}, respectively.

A decision feedback equalizer may reorder the received substreams byrearranging the rows and columns of H. For example, a layered processingapproach may be employed. Symbols are detected sequentially andinterference from previously detected symbols is subtracted. Receivedvector elements are weighted to null (or reduce) interference fromundetected symbols.

Method and apparatus implementations of radio transceivers in accordancewith aspects of the disclosure, such as radio transmission techniquesand radio transmitters employed by UEs and/or base transceiver stations,are depicted in the block diagram of FIG. 14A. The blocks disclosedherein can be steps of a method, functional blocks of a transmitterand/or transmitter system, and/or components of a transmitter and/ortransmitter system. In some aspects of the disclosure, such as disclosedin the '850 and '163 applications, a transmitter's components can resideon different devices, such as on different network devicescommunicatively coupled together via a network.

An exemplary aspect of the disclosure provides for OFDM signaling. Aninformation signal s(t) is encoded and/or interleaved in block 1401.Various types of coding that are known in the art can be employed. Forexample, in the uplink, it can be desirable to produce a transmissionsignal with low dynamic range (i.e., peak to average power). Thus, theUEs can employ CI coding on OFDM subcarriers to produce CI-OFDM (alsoknown as a single-carrier OFDM) signals.

The coding/interleaving block 1401 can provide for generating orotherwise acquiring symbol values to be impressed onto the subcarriers.The information signal can be provided with predetermined trainingsymbols in a training symbol injection block 1402. Training symbols canbe used for various purposes, including, but not limited to, channelestimation, signal-quality estimation, and synchronization.

An IFFT 1403 (or equivalent process) impresses the coded data symbolsonto the subcarriers and adds a cyclic prefix. FIR filtering andinterpolation 1404 is performed prior to preparing the resulting signalfor transmission into a communication channel, typically via an RF frontend (not shown).

Various methods and systems adapted to perform the blocks shown in FIG.14A can be provided by transmission systems and methods pertaining tothe aspects and embodiments of the disclosure. Furthermore, variousother signal-processing steps that are typically performed in radiotransmitters may be included herein. For example, pre-equalization stepsand/or systems may be included in the transmission methods andtransmitters disclosed herein.

As described throughout the disclosure, array processing may beperformed in transmitters and in transmission methods. Array processing(e.g., subspace multiplexing) can be performed after FIR filtering andinterpolation 1404. In some aspects, array processing can be integratedinto the coding 1401, IFFT 1403, and/or FIR filtering 1404 blocks.

As used herein, RAN baseband processing is the Physical Layer processingof baseband signals, such as digital baseband signals that will betransmitted in the RAN (after DAC and up-conversion), and digitizedbaseband signals produced from received radio signals in the RAN. RANbaseband processing is distinguished from IP processing in that RANbaseband processing is particular to the RAN. By way of example, FIRfiltering 1404, modulation (e.g., IFFT 1403), and training signalinjection 1402 are RAN baseband processes. Coding 1401 can includePhysical Layer and/or higher layers. For example, forward-errorcorrection (FEC) is often employed by the data link layer or higher. Itshould be appreciated that RAN baseband processing includes RAN multipleaccess and RAN spread spectrum coding, but not transcoding. Interleaving1401, as it pertains to distributing data symbols over a physicalresource (e.g., multiplexing data symbols on selected bins of a Fouriertransform) constitutes RAN baseband processing, whereas interleavingdata bits in a data stream does not. Many base station networkcoordination processes, such as scheduling, hand-over, routing, powercontrol, and control signaling, are not RAN baseband processingoperations. While channel estimation is a RAN baseband processingoperation, conveying channel estimates, SNRs, or BERs between basestations is not. While multiple access and multiplexing (i.e.,generating the physical signals wherein data is partitioned by timeinterval, frequency, code space, etc.) constitutes RAN basebandprocessing, assigning network resources to UEs does not.

Method and apparatus implementations of radio transceivers in accordancewith aspects of the disclosure, such as radio reception techniques andradio receivers employed by UEs and/or base transceiver stations, aredepicted in the block diagram of FIG. 14B. The blocks disclosed hereincan be steps of a method, functional blocks of a receiver and/orreceiver system, and/or components of a receiver and/or receiver system.In some aspects of the disclosure, such as disclosed in the '850 and'163 applications, a receiver's components can reside on differentdevices, such as on different network devices communicatively coupledtogether via a network.

Signals received from a communication channel are input to an FIRfiltering and decimation block 1405. Filtered signals may be processedin a synchronization step 1411 to control the timing of variousreception processes, such as, but not limited to, a cyclic prefixremoval and FFT step 1406 and array processing 1407. Complex-amplitudemeasurements associated with individual subcarriers, such as estimatesobtained via known training symbols and/or unknown data symbols, may beused in a channel-estimation step 1413. The channel estimation step 1433can facilitate the generation of weights (e.g., array-processing and/orCI combining weights).

Array processing 1407 is performed to achieve some preferred combinationof system capacity (e.g., subspace demultiplexing) and signal quality(e.g., diversity combining). For example, array processing 1407 mayinclude spatial interferometry multiplexing and/or any other form ofarray processing. In some aspects, array processing 1407 may be assistedby an interference-estimation step 1416. CI combining 1418 may beperformed in conjunction with the array-processing 1407 and/or adecoding and de-interleaving 1408. Alternatively, either or both thearray-processing 1407 and the decoding and de-interleaving 1408 mayperform CI combining 1418. The decoding and de-interleaving step 1408performs any necessary de-interleaving of data symbols received from thearray-processing 1407 prior to, or following decoding 1408. Decoding1408 can include channel, multiple access, spread spectrum, encryption,and/or other decoding processes.

FIG. 15 is a block diagram of a transceiver in accordance with someaspects of the disclosure. A receiver system 1501 is configured tocouple a received signal from a communication channel. One or moretypical receiver-side signal processing techniques (such as filtering,mixing, down conversion, amplification, A/D conversion, etc.) may beperformed on the received signal. A filter bank, such as an FFT 1502,separates the received signal into a plurality of frequency components.If the received signal is an OFDM signal, the FFT 1502 retrieves asymbol measurement for each OFDM subcarrier. The components are providedwith weights in a receiver weighting system 1503. The weights mayinclude one or more types of weights, such as channel-compensationweights, decoding weights, spatial de-multiplexing weights, multi-userdetection weights, array-processing weights, wavelet-processing weights,etc. The weighted components are combined in a combiner 1504. Thecombined signals may be processed in a data processor 1505. In someaspects, the data processor 1505 may be part of a blind-adaptiveprocessor 1506 that is adapted to generate and/or adapt weights relativeto one or more performance parameters, such as channel estimates,confidence measures, data estimates, signal power, probability of error,BER, SNR, SNIR, etc.

In one aspect, the blind-adaptive processor 1506 processesinformation-bearing CI symbol measurements produced by the FFT 1502. Theprocessor 1506 may work in conjunction with the combiner 1504 to combinethe measurements and estimate transmitted data. In some aspects, thecombining process may include wavelet processing. The processor 1506 maywork in conjunction with the data processor 1505 to provide a channelestimate based on data estimates. In some aspects, the processor 1506can employ a time-varying channel-estimation filter. In some aspects,the processor 1506 provides channel compensation, which may be based ona statistical characterization of interference, such as a covariancematrix.

In some applications, the processor 1506 provides predistortion (i.e.,pre-coding) weights to transmitted signals. A data stream is optionallyprocessed by a transmit data processor 1507. A transmitter weightingsystem 1508 is configured to weight data symbols provided to frequencybins of a frequency-domain-to-time-domain converter, such as an IFFT1509. Time-domain signals generated by the IFFT 1509 are provided to atransmission system configured to prepare the time-domain signals fortransmission into a communication channel.

In accordance with aspects of the disclosure, transceiver operatingcharacteristics can be adaptable, such as indicated in the block diagramdepicted in FIG. 16. In one aspect, a control circuit 1601 is configuredto receive one or more system requirements 1611 and, optionally, one ormore channel characteristics 1612. The control circuit 1601 can adaptone or more signal parameters 1602 employed by a radio transceiver 1603,such as radio transceivers employed by UEs, base transceiver stations,and/or central processors. Signal parameter adaptation and/or selectionaffect one or more transceiver operating parameters 1621.

In one aspect, the control circuitry 1601 may scale a transmitted bitrate by scaling the symbol duration, the number of subcarriers, thesubcarrier spacing, and/or the number of bits per symbol per subcarrier.This permits the transceiver 1603 to operate in different communicationsenvironments, which may require varying operating parameters and/orcharacteristics. By adapting the operating parameters and/orcharacteristics of the transceiver 1603, the control circuitry 1601 candynamically change the radio signals, thereby providing forcompatibility or improving performance. For example, dynamically scalingthe bit rate enables widely varying signal bandwidths, adjustment ofdelay-spread tolerances, and adaptability to different SNR requirements.An adaptable transceiver system can be particularly useful for mobilewireless communications, as well as other applications that support avariety of services in a variety of environments.

In accordance with some aspects of the disclosure, an OFDM system may beconfigured to select the number of subcarriers and a variable symbolduration. The control circuitry can dynamically select the number ofsubcarriers to decrease the signal bandwidth and the transmission ratewhile delay-spread tolerance remains the same. The control circuitry1601 can also dynamically increase the symbol duration to decrease thetransmission rate and the signal bandwidth and provide an increase indelay-spread tolerance. In some aspects, the control circuitry 1601 canbe adapted to adjust the transmission rate by changing the type ofmodulation. In accordance with other aspects, variable transmissionrates can be achieved by using adaptive coding wherein different codingschemes are selected to improve the link reliability and/or to decreasethe peak-to-average power ratio.

In accordance with yet other aspects of the disclosure, adaptabletransmission rates permit asymmetric data rates throughout the network.For example, individual UEs can be allocated varying sets of subcarriersdepending on their data bandwidth needs. Additionally, during datadownloading, for example, a mobile unit could have a larger downlinkdata rate than uplink data rate.

In accordance with some aspects of the disclosure, base transceiverstations employ adaptive antenna processing wherein UEs feedback theirchannel estimates via the uplink when uplink and downlink channelcharacteristics are not identical. In some aspects, power control can beperformed on individual subcarriers or on groups of subcarriers.Alternatively, or in addition to power control, certain subcarriers maybe selected to optimize one or more operational parameters, such asthroughput, probability of error, received signal power, transmitterpower efficiency, SNR, QOS, etc.

Sets of subcarriers may be selected with respect to the types ofservices being provided. For example, different qualities of servicecorresponding to different-priority links and/or different link servicesmay be criteria for selecting subcarriers. In one case, subcarriershaving little distortion and interference may be selected for services(such as data links) that do not tolerate high BER. In another case, atransmission may be divided into sections and sent on two or more groupsof subcarriers (or channels). In some aspects, a more important section,such as addressing information, may be sent on higher-qualitysubchannels than subchannels on which payload data is sent. Addressingand other control information is typically less tolerant to errors thanpayload data. Thus, important parts of a transmission may be transmittedon higher-quality subspaces and/or on subcarriers having littledistortion and fading.

In some aspects of the disclosure, various demand-assigned protocolsgovern the utilization of the bus medium. As used herein, the term busmedium, or bus, refers to a communication system or communicationresources employed to communicatively couple together distributedtransceiver components in a manner that resembles the functions of acomputer bus. This expression covers all related hardware components(wire, optical fiber, etc.) and software, including communicationprotocols. By way of example, a bus can comprise a fronthaul network, abackhaul network, a local area network, and/or a wide area network. Inone aspect, a bus communicatively couples together internal componentsresiding in different networked devices, wherein the internal componentsare configured (such as by a central processor or via some distributedprocessing means) to function together as a single transceiver ortransceiver system. In such aspects, a bus can comprise communicationpathways, internal networks, etc. inside the networked devices.

As disclosed herein, software instructions configured to perform methodsin accordance with aspects of the disclosure can provide variouscombinations of object-oriented design features. For example, a radiotransceiver system comprising multiple components distributed acrossmultiple networked devices may be provided with an abstraction interfacewherein the multiple different constituent components are mapped to asingle abstract device. Thus, the details of how the radio transceiversystem is implemented (for example, whether the radio transceiver is asingle discrete device or comprised of multiple constituent componentscommunicatively coupled together via a bus) can be hidden from systemsand operations configured to employ the radio transceiver system. In oneexample, MIMO processing algorithms can be employed across the multipleconstituent components in substantially the same manner as would beemployed in a single device comprising multiple antennas. As describedherein, MIMO processing algorithms can include various types ofalgorithms, including, but not limited to, MRC, MMSE, ZF, and/orsuccessive interference cancellation. In some aspects, certain detailsof the radio transceiver system implementation are provided to theabstract device. For example, certain implementation details (or atleast the effects of the implementation) can help a MIMO processorcompensate for latencies in the bus communications between cooperatingdevices in a Cooperative-MIMO configuration.

In accordance with one aspect of the disclosure, each data communicationdevice (DCD) of a set of DCDs in a network communicates with a centralaccess point (AP). Multiple DCDs may request access from the AP in thesame request access (RA) burst. In one aspect, each of the multiple DCDstransmits its access request to the AP within a frequency-domainsubchannel in the RA burst that is orthogonal to the frequency domainsubchannels used by the other DCDs requesting access. In another aspect,each of the multiple DCDs transmits its access request to the AP withina subspace channel in the RA burst that is orthogonal to the subspacechannels used by the other DCDs requesting access. Alternatively, otherorthogonal diversity-parameter values may be employed. In some aspects,each DCD provides channel training information in the RA burst to allowthe AP and/or DCD to adapt to variations in channel characteristics.

FIG. 17 is a block diagram depicting a plurality K of UEs 120.1-120.K(e.g., mobile or fixed subscriber units) in a wireless networkcomprising a plurality N of base transceiver stations (e.g., accesspoints) 101.1-101.N. At least one of the UEs 120.1-120.K is configuredto transmit a pilot signal or known training signal that is received atthe base transceiver stations 101.1-101.N. The propagation environmentensures that the set of pilot signals received by the base transceiverstations 101.1-101.N is unique for each UE's 120.1-120.K location. Insome aspects of the disclosure, the uniqueness of the propagationenvironment can be exploited to provide or enhance coding. The basetransceiver stations 101.1-101.N are adapted to process the receivedpilot signals. Processing operations may depend on variouscharacteristics of the received pilot signals, including absolute and/orrelative signal power levels. For example, a predetermined set of thebase transceiver stations 101.1-101.N may be selected to process signalsfor a given UE based on the received pilot signal power.

In one aspect, at least one of the base transceiver stations 101.1-101.Nis configured to perform channel analysis to characterize thepropagation environment of the transmissions between each UE 120.1-120.Kand the base transceiver station(s) 101.1-101.N. Channel analysis mayinclude delay-profile and/or flat-fading characterizations. In someaspects of the disclosure, the propagation environment is employed as aunique identifier for each UE 120.1-120.K. In some aspects, weightscalculated from channel estimates may be utilized in multiple-accesscodes, encryption codes, and/or authentication and verificationprocedures.

In some aspects of the disclosure, channel analysis is used to generatefilter weights and/or array-processing weights at the base transceiverstations 101.1-101.N to process received and/or transmitted signals.Such weights may be generated using various algorithms, such as MRC,MMSE, ZF, and/or successive interference cancellation, as well asothers. The base transceiver stations 101.1-101.N may comprisesingle-antenna systems or multi-antenna systems, such as antenna arrays.Received signals may be compared to some local or global timingreference, such as to analyze phase offsets and/or signal timing.

In another aspect of the disclosure, the base transceiver stations101.1-101.N are configured to transmit pre-coded signals to the UEs120.1-120.K. For example, the transmissions can be pre-coded to exploitthe multipath environment between the access points 10011 to 10015 andthe UEs 120.1-120.K to constructively combine at the UEs 120.1-120.K.

In one set of aspects, transmission (i.e., pre-coding) weights aregenerated from the reciprocal of a channel matrix that characterizes thepropagation environment between a plurality of the base transceiverstations 101.1-101.N and at least one of the UEs 120.1-120.K. Channel(i.e., pre-coding) weights may be generated via any combination ofdeterministic (i.e., training) and blind-adaptive processing. Channelweights may be selected and/or adapted to optimize coherent combining ofthe base transceiver stations' 101.1-101.N transmissions at one or moreof the UEs 120.1-120.K. Similarly, the channel weights may be selectedand/or adapted to optimize coherent combining of signals received by thebase transceiver stations' 101.1-101.N from one or more of the UEs120.1-120.K. Any of various combining techniques may be employed.

In some aspects, channel weights are adapted to generate beam-patternnulls at one or more of the UEs 120.1-120.K or other transceivers.Channel weights may be adapted to provide time-varying channelcompensation. Thus, beam steering, null steering, or any othertime-dependent adaptive array processing may be performed. Appropriatecombinations of carrier selection and carrier weighting may be providedto achieve simultaneous directionality (e.g., spatial multiplexing) anddiversity benefits. In some applications, any of the base transceiverstations 101.1-101.N may be replaced by UEs configured to function asrouters, relays, and/or array elements of an adaptive transceiver array.

FIG. 18 is a block diagram of a RAN comprising base transceiver stations101.1-101.N configured in accordance with an aspect of the invention.The fronthaul network 105 can comprise a wireless, fiber optic, and/orwireline network that communicatively couples the base transceiverstations 101.1-101.N to a central processor 110. The central processor110 is configured to process signals received from and transmitted bythe base transceiver stations 101.1-101.N.

In accordance with one aspect of the disclosure in the '163 application,the central processor 110 comprises a distributed computing system 111.In accordance with another aspect of the disclosure in the '163application, the central processor 110 is replaced by the distributedcomputing system 111. In one aspect, the distributed computing system111 comprises a plurality of processors, which may be geographicallydistributed. As used herein, the term “processor” can refer to acomputer processor, a computer, a server, a central processing unit(CPU), a core, a microprocessor, and/or other terminology that indicateselectronic circuitry configurable for carrying out instructions of acomputer program.

The processors are communicatively coupled together via at least onenetwork, such as a backhaul network 115. The backhaul network 115 cancomprise an optical fiber network, a wireline network (e.g., Ethernet orother cable links), a wireless network, or any combination thereof. Inone aspect, the processors are programmed to function as a plurality Nof virtual base stations 111.1-111.N. By way of example, each virtualbase stations 111.1-111.N may comprise one or more of the processors andperform base station processing operations that would ordinarily beperformed by one or more of the corresponding base stations 101.1-101.N.Specifically, virtual base stations can be implemented via software thatprograms general-purpose processors. For example, an SDR platformvirtualizes baseband processing equipment, such as modulators,demodulators, multiplexers, demultiplexers, coders, decoders, etc., byreplacing such electronic devices with one or more virtual devices,wherein computing tasks perform the functions of each electronic device.In computing, virtualization refers to the act of creating a virtual(rather than actual) version of something, including (but not limitedto) a virtual computer hardware platform, operating system (OS), storagedevice, or computer network resources.

In accordance with the art of distributed computing, a virtual basestation's functions can be implemented across multiple ones of theplurality of processors. For example, workloads may be distributedacross multiple processor cores. In some aspects, functions for morethan one base station are performed by one of the processors.

As used herein, distributed computing refers to the use of distributedsystems to solve computational problems. In distributed computing, aproblem is divided into multiple tasks, and the tasks are solved bymultiple computers which communicate with each other via messagepassing. A computer program that runs in a distributed system isreferred to as a distributed program. An algorithm that is processed bymultiple constituent components of a distributed system is referred toas a distributed algorithm. In a distributed computing system, there areseveral autonomous computational entities, each of which has its ownlocal memory.

In accordance with aspects of the disclosure, the computational entities(which are typically referred to as computers, processors, cores, CPUs,nodes, etc.) can be geographically distributed and communicate with eachother via message passing. In some aspects, message passing is performedon a fronthaul or backhaul network. The distributed computing system canconsist of different types of computers and network links, and thesystem (e.g., network topology, network latency, number of computers,etc.) may change during the execution of a distributed program. In oneaspect, a distributed computing system is configured to solve acomputational problem. In another aspect, a distributed computing systemis configured to coordinate and schedule the use of shared communicationresources between network devices.

A distributed computing system can comprise a grid computing system(e.g., a collection of computer resources from multiple locationsconfigured to reach a common goal, which may be referred to as a supervirtual computer). In some aspects, a distributed computing systemcomprises a computer cluster which relies on centralized management thatmakes the nodes available as orchestrated shared servers. In someaspects, a distributed computing system comprises a peer-to-peercomputing system wherein computing and/or networking comprises adistributed application architecture that partitions tasks and/orworkloads between peers. Such distributed peer-to-peer computing systemsare disclosed in the '107 application. In some aspects, peers areequally privileged, equipotent participants in the application. They aresaid to form a peer-to-peer network of nodes. Peers make a portion oftheir resources, such as processing power, disk storage, networkbandwidth, etc., available to other network participants without theneed for central coordination by servers or stable hosts. Peers can beeither or both suppliers and consumers of resources.

As disclosed in the patents and patent applications incorporated byreference herein, and particularly with respect to aspects ofCooperative-MIMO systems and methods, network nodes can function aseither or both clients and servers. Furthermore, when wireless networknodes cooperate in subspace processing, they create network resources,such as subspace (i.e., spatial multiplexing) channels, performancegains, RAN coverage area, etc. Even when UEs cooperate as a client array(e.g., a UE cluster) in a Cooperative-MIMO implementation, each UE canimprove the data bandwidth, quality of service, range, and powerefficiency of the other UEs in the array, or cluster. Thus, in someaspects of a Cooperative-MIMO system, UEs can extend the networkinfrastructure, such as to increase per-client data bandwidth, thenumber of clients served, coverage area, and/or quality of servicewithout requiring substantial capital outlays from network operator toupgrade the base station network.

In Cooperative-MIMO systems, mobile UEs can opportunistically jointogether via a peer-to-peer overlay network for client-side MIMOprocessing. In some aspects, UEs can join base transceiver arrays via anoverlay network to assist in server-side MIMO processing. Due to randommovement of UEs, aspects of the invention do not impose a particularstructure on the overlay network. Because there is no structure globallyimposed upon them, unstructured networks are easy to build and allow forlocalized optimizations to different regions of the overlay. Also, insome aspects, because the role of all peers in the network is the same,unstructured networks are highly robust in the face of high rates ofchurn (i.e., when peers are frequently joining and leaving the network).

In accordance with some aspects of the disclosure, the base transceiverstations 101.1-101.N are “dumb terminals,” wherein base station signalprocessing (for example, the baseband processing) is performed by thecentral processor 110 (which may include the distributed computingsystem 111). Thus, in some aspects, the base transceiver stations101.1-101.N are simply radio remote units. For example, the basetransceiver stations 101.1-101.N might perform only basicsignal-processing functions, such as RF processing (i.e., radiofront-end processing), which can include frequency conversion and(optionally) ADC/DAC functions, while the central processor 110 (whichmay include the distributed computing system 111) performs basebandprocessing, including channel analysis and generating base transceiverMIMO weights.

In one aspect, the central processor 110 coordinates or performsbaseband signal processing corresponding to base station operations,whereas the base transceivers 101.1-101.N provide only RF front endsignal processing, including frequency conversion, and optionally,ADC/DAC. The central processor can perform waveform shaping, errordetection, error correction, power control, channel selection, multipleaccess control, multiplexing, modulation, formatting, synchronization,coding, etc. for the plurality of base transceivers (i.e., accesspoints) communicatively coupled to the central processor via thefronthaul network. In some aspects of the disclosure, the centralprocessor 110 provides for base-station functionality, such as powercontrol, code assignments, and synchronization. The central processor110 may perform network load balancing, including providing forbalancing transmission power, bandwidth, and/or processing requirementsacross the radio network. Centralizing the processing resources (i.e.,pooling those resources) facilitates management of the system, andimplementing the processing by employing multiple processors configuredto work together (such as disclosed in the '163 application) enables ascalable system of multiple independent computing devices, wherein idlecomputing resources can be allocated and used more efficiently.

Some aspects allow base station processing resources (e.g., theprocessors in the distributed computing system 111) and the remote RFunits (e.g., the base transceiver stations 101.1-101.N) to be deployedseparately. For example, RAN coverage, capacity, and/or data bandwidthper UE can be improved by adding base transceiver stations, and then theSDR platform dynamically adapts to the new RAN base stationconfiguration. Similarly, the SDR platform can adapt to the loss of oneor more of the base transceiver stations 101.1-101.N. The distributedcomputing system (e.g., cloud network) 111 can adapt to varyingprocessing loads by allocating computing resources as needed.Furthermore, system upgrades, such as new transmission protocols, can beeasily implemented via software upgrades to the SDR platform.

In some aspects, base-station functionality is controlled by individualbase transceiver stations and/or UEs assigned to act as base stations.Array processing may be performed in a distributed sense wherein channelestimation, weight calculation, and optionally, other network processingfunctions (such as load balancing) are computed by a plurality ofspatially separated processors. In some aspects, access points and/orsubscriber units are configured to work together to performcomputational processing. A central processor (such as central processor110) may optionally control data flow and processing assignmentsthroughout the network.

As disclosed in the '850 application, the system depicted in FIG. 18provides system performance benefits by centralizing (e.g., pooling)much of the equipment (and/or signal processing) typically employed atthe cell sites. Cost reduction is another motivation for centralizingthe radio access network, as most of a cellular network's ownershipcosts comprise operating costs, including site rental, power, andsupport and maintenance expenses. Thus, instead of distributing basebandprocessing equipment at the edge of the network as in conventionalcellular networks, centralizing the radio access network at the centralprocessor 110 can greatly reduce capital expenditures to build out andupgrade the radio access network, as well as reduce operatingexpenditures.

As disclosed in the '163 application, providing for distributedcomputing at the central processor 110 provides network functionvirtualization to the radio access network. Benefits that can berealized with some aspects of the disclosure include cost reduction frompooling and virtualizing baseband processing. This can eliminate theneed to provision for peak capacity on a per-site basis, thus reducingprocessing requirements. Furthermore, instead of requiring dedicatedbase station hardware, some of the disclosed aspects provide for the useof commercial (e.g., general-purpose) servers running software.

As disclosed in the patents and applications incorporated by referenceherein, other types of networks, including wireless networks, canconnect the base transceiver stations 101.1-101.N. One of the advantagesof employing the optical fiber fronthaul 105 is that optical fiber canprovide the high capacity and low latency required by many aspects ofthe invention. For example, when a large number of baseband processorsare co-located at the central processor 110, the amount of databandwidth in the fronthaul and the synchronization requirements betweenbase transceiver stations 101.1-101.N can increase substantially whenhigh RF bandwidth and MIMO are employed. Different aspects of theinvention can provide for different functional splits betweencentralized and distributed functions.

Some aspects of the invention can reduce fronthaul requirements byimplementing at least some of the Physical Layer processing at the basetransceiver stations 101.1-101.N while implementing other processing(e.g., higher layer processing, or the higher layer processing plus someof the Physical layer processing) at the central processor 110. Thus, insome aspects of the invention, one or more of the base transceiverstations 101.1-101.N depicted in the figures may be replaced by UEsadapted to perform as routers, repeaters, and/or elements of an antennaarray.

In one aspect of the disclosure, the base station network comprisingbase transceiver stations 101.1-101.N is adapted to operate as anantenna array. In such aspects, a portion of the network may be adaptedto serve each particular UE. The central processor 110 and/or the basetransceiver stations 101.1-101.N may be configured to perform othersignal-processing operations, such as, but not limited to, waveformshaping, error detection, error correction, power control, channelselection, multiple access control, multiplexing, modulation,formatting, synchronization, coding, etc. In some aspects of thedisclosure, the central processor 110 is replaced by a distributedcomputing system. In some aspects, the distributed computing system maycomprise a plurality of the UEs 120.1-120.K, repeaters (not shown),and/or the base transceiver stations 101.1-101.N.

FIG. 19 is a block diagram that depicts apparatus and method aspects ofthe disclosure. Access points (e.g., access point 1901) and at least oneaccess controller (e.g., central processor 1902) are connected via afronthaul network 1905, which may comprise an optical fiber, wireless,and/or wireline network. In some aspects, the fronthaul network 1905 maycomprise standard interfaces, such as Common Public Radio Interface(CPRI) or Open Base Station Architecture Initiative (OBSAI). The accesspoint 1901 comprises radio processing equipment 1910, and the centralprocessor 1902 comprises baseband processing equipment 1920.

In accordance with some aspects of the disclosure, the entire basebandprocessing is carried out in the central processor 1902 while there maybe no baseband processing performed at the access points 1901. Forexample, the radio processing equipment 1910 may comprise analog frontend circuitry and digital front end circuitry, and the basebandprocessing equipment 1920 comprises circuitry for the layers L1 (i.e.,the Physical Layer) and higher layers. In one aspect of the invention,the radio processing equipment 1910 may perform basic signal-processingtasks, such as amplification, RF filtering, frequency conversion, aswell as other RF signal-processing functions. The baseband processingequipment 1920 may perform baseband processing, includingmodulation/demodulation, combining, channel characterization, powercontrol, other system control functions, quality factor analysis,coding, array processing etc.

It should also be appreciated that in some aspects, such as supported bythe disclosures of the patents and patent applications that areincorporated by reference, that either or both radio processingequipment 1910 and the baseband processing equipment 1920 may each beimplemented with one or more processors and one or more memoriesincluding computer program code, the computer program code comprisinginstruction configured to cause the processor(s) to perform thecorresponding radio processing and/or baseband processing functions.

In accordance with some aspects of the disclosure, physical-layerbaseband processing is performed on an SDR platform, which can beimplemented on a distributed (e.g., cloud) computing system.Physical-layer baseband processing can include multiplexing,de-multiplexing, modulation, de-modulation, and/or equalization.

In one aspect of the invention, the access point 1901 is a device thatserves as the air interface to the user equipment and implements analogradio frequency functions of an eNodeB. The access point 1901 mayinclude one or more antennas for communicating with one or more UEs, andmay include support for a variety of antenna types and configurationsincluding, but not limited to, single omni-directional antennas and MIMOarrays of directional antennas. Exemplary functions that may beperformed by the access point 1901 include digital-to-analog (D/A)conversion, analog-to-digital (A/D) conversion, carrier multiplexing,power amplification, and RF filtering. The central processor 1902 may bean LTE network device configured to implement radio functions of thedigital baseband domain. These functions may include, but are notlimited to, radio base station control and management, MIMO processing,and channel coding and de-coding.

FIG. 20A is a flow chart depicting methods in accordance with aspects ofthe disclosure. Each of a plurality of geographically distributed accesspoints performs RF processing of signals received from UEs in a radioaccess network 2001, such as a WWAN. The resulting RF-processed signalsare communicated to a central processor via a fronthaul network 2002,such as an optical fiber network. The central processor collectsRF-processed signals from the plurality of geographically distributedaccess points 2003 and performs baseband processing of the collectedsignals 2004. In one aspect of the disclosure, the baseband processing2004 comprises distributed computing performed by a distributedcomputing system. For example, the central processor may configure aplurality of processors to perform baseband processing.

FIG. 20B is a flow chart depicting methods in accordance with aspects ofthe disclosure. A central processor performs baseband processing of UEsignals 2011 to be transmitted by a plurality of geographicallydistributed access points to UEs served by a radio access network. Inone aspect of the disclosure, the baseband processing 2011 comprisesdistributed computing performed by a distributed computing system (e.g.,a cloud). For example, the central processor may configure a pluralityof processors to perform baseband processing.

The resulting baseband-processed signals are communicated to theplurality of geographically distributed access points via a fronthaulnetwork 2012. The central processor may coordinate the plurality ofgeographically distributed access points to transmit signals in theradio access network to the UEs 2013. Each of the access points performsRF processing of the baseband-processed signals 2014 prior totransmitting the signals to the UEs.

In some aspects of the disclosure, the access point antennas areconnected to the central processor via optical fiber. Various types offronthaul networks may be employed, including optical fiber, wireline(e.g., cable), wireless (e.g., radio), and any combination thereof. Inwireless backhaul networks, such as those disclosed in the '163application, digitized RF signals from various nodes can be aggregated,which allows the building of networks in chain, tree, and ringtopologies.

In some aspects, the access point antennas can be considered as radioremote units, and the central processor can be considered as a centralhub unit. The baseband signals from multiple access points can begathered and processed together in the central processor to providedistributed antenna system MIMO benefits, such as spatial multiplexinggain. Similar types of distributed antenna system MIMO processing (e.g.,pre-coding) can be performed at the central processor for signals to betransmitted by the access points.

In one aspect of the disclosure, downlink data is transmitted via MRCspatial multiplexing with power control. It should be appreciated thatdifferent aspects can effect various types of combining via pre-codingconfigured with respect to signal propagation measurements in the RANchannel. Pre-coding may comprise MRC, ZF, MMSE, and/or any of a varietyof adaptive techniques, including blind adaptive techniques disclosed inthe '163 and '107 applications. Coding and power control can compriseopen-loop and closed-loop methods. In some aspects, UEs may be selectedby the central processor and scheduled for array processing based onquality metrics (e.g., channel conditions, power measurements, SNR,etc.).

In accordance with some aspects of the disclosure, a network topology isdepicted in FIG. 21 comprising a source node 2100, a destination node2105, and a plurality of intervening nodes 2102.1-2102.P. The networknodes 2100, 2105, and 2102.1-2102.P may comprise UEs and/or basetransceiver stations. The network nodes 2102.1-2102.P and anyintervening nodes (not shown here, but depicted in the drawings of the'163 application) may be configured to function as routers and/orrelays.

In accordance with some aspects of the disclosure, as the networkevolves, the nodes adapt their routing tables. As network loads change,the nodes can perform load balancing, such as to ensure a predeterminedrange of bandwidth and transmit-power loads across the network. One ormore paths to the destination node 2105 can be selected or modified tooptimize loads across the network, minimize transmission power, and/orensure received signal quality. In one aspect of the disclosure,multiple transmission paths to the destination node 2105 are employed toachieve one or more objectives, such as reducing the effects of fading,reducing transmission power in some of the relays, and/or distributingtransmission power across the network.

Information intended for the destination node 2105 can be passed throughthe network along one or more intervening nodes 2102.1-2102.P. One ormore of the intervening nodes (e.g., nodes 2102.1-2102.P) can provide afinal radio link to the destination node 2105. For the sake ofsimplicity, FIG. 21 depicts a plurality P of transmission paths2101.1-2101.P from the source node 2100 to the intervening nodes2102.1-2102.P. It should be appreciated that each transmission path cancomprise multipath components. It should be appreciated that in someaspects, one or more intervening nodes (not shown) may be utilizedbetween the source node 2100 and nodes 2102.1-2102.P.

The source node 2100 comprises an antenna system 2110, which may includeone or more antennas. Similarly, each of the intervening nodes2102.1-2102.P comprises an antenna system (2120.1-2120.P, respectively)which may include one or more antennas. When multiple antennas areemployed by a node (e.g., nodes 2100, 2105, and/or 2102.1-2102.P), thenode may perform any combination of diversity processing and spatialmultiplexing with respect to its antenna system.

In accordance with one aspect of the invention, the source node 2100selects a plurality P of the intervening nodes 2102.1-2102.P to providecooperative subspace processing, such as to increase the rank of thesubspace pre-coding matrix and increase the number of linearlyindependent coded transmissions. In a first aspect of the disclosure,the transmission paths 2101.1-2101.P comprise the radio access network.In a second aspect of the disclosure, the transmission paths2101.1-2101.P comprise a fronthaul network. In both the first and secondaspects, the intervening nodes 2102.1-2102.P comprise antennas of aCooperative-MIMO antenna array.

As depicted in FIG. 21, a plurality P of the intervening nodes2102.1-2102.P can be selected to provide a final RF link (e.g.,transmission paths 2103.1-2103.P) to the destination node 2105. Itshould be appreciated that each transmission path can comprise multipathcomponents. It should be appreciated that in some aspects, one or moreintervening nodes (not shown) may be utilized between the source node2100 and nodes 2102.1-2102.P.

In one aspect, the destination node 2105 selects the plurality P of theintervening nodes 2102.1-2102.P to increase the number of linearlyindependent coded transmissions it receives, effectively increasing therank of the matrix that encodes the transmitted data. In one aspect ofthe disclosure, the transmission paths 2103.1-2103.P comprise the radioaccess network, and the antenna system 2115 comprises a spatialmultiplexing system configured to perform subspace processing. Inanother aspect of the disclosure, the transmission paths 2103.1-2103.Pcomprise a fronthaul network, and the intervening nodes 2102.1-2102.Pcomprise antennas of a Cooperative-MIMO antenna array.

In one aspect, the transmitted signals comprise multiple addressescorresponding to at least one path from the source node 2100 to thedestination node 2105. The transmission may include multiple addressescorresponding to a plurality P of devices (e.g., nodes 2102.1-2102.P)that provide the final RF link to the destination node 2105.Alternatively, the transmission may include only the destination addressof the destination node 2105. More than one destination address may beincluded for a particular transmission. A transmission may be duplicatedwhen paths diverge. For example, a message with addresses to nodes2102.1-2102.P can be duplicated by node 2100. In some aspects, abroadcast message includes a plurality of addresses, and the network isconfigured to propagate a single version of the message to all of theaddresses.

In accordance with one aspect disclosed in the '163 application, a datamessage is provided that includes a plurality of destination addresses.Processing instructions, such as transmission weight values (e.g., apre-coding matrix), are included with the data message. A single copy ofthe message is routed through nodes that form a path that is common toall of the destination addresses. The message is duplicated where thepaths to the destination addresses diverge, but different linear codingis applied to the message for each of the paths. As disclosed in the'163 application, each router or relay can provide its own unique linearcodes to the messages that pass through it.

The codes may include any combination of polyphase CI codes, CI-basedcodes, and channel-specific spatial interferometry codes (e.g., linearcodes based on the random channel). For example, the channelcharacteristics for each transmission path (2101.1-2101.P and/or2103.1-2103.P) can be exploited to provide addressing and/ormultiple-access coding. Coding may include space-time coding,space-frequency coding, polarization coding, etc.

Some aspects of the disclosure provide for CI codes that can beimplemented across one or more diversity-parameter spaces. Similar torandom linear codes, all CI codes of a given set of CI code words can beconstructed from a combination of linearly independent code vectors thatform the CI code generation matrix. A CI coder is configured to generatea plurality of algebraically unique linear combinations of a pluralityof information signals.

FIG. 22A depicts an aspect of the disclosure wherein at least the sourcenode 2100 transmits a plurality P of transmit messages t₁, t₂, . . . ,t_(P) on the plurality P of network paths 2101.1, 2101.2, . . . ,2101.P, respectively to the plurality P of intervening nodes (e.g.,nodes 2102.1, 2102.2, . . . , 2102.P). In one aspect, each of thetransmit messages t₁, t₂, . . . , t_(P) comprises a unique linearcombination of P information messages (or symbols) x₁, x₂, . . . ,x_(P). For example, a p^(th) transmit message t_(p) may employ a vectorof coefficients [α_(p,1), α_(p,2), . . . , α_(p,P)] that is a row orcolumn of a code matrix having rank P. In one aspect disclosed in the'163 application, the code matrix (e.g., channel-specific coding)comprises space-time or space frequency codes (e.g., pre-coding), suchas derived from channel measurements. The characteristic randomness ofthe P terrestrial wireless transmission paths (e.g., 2101.1-2101.P) canprovide a code matrix of random values with rank P if the transmissionpaths 2101.1-2101.P are sufficiently uncorrelated.

In one aspect, the source node 2100 selects the transmission paths2101.1-2101.P to build up the rank of the code matrix. For example, thesource node 2100 selects a sufficient number of the intervening nodes2102.1-2102.P to ensure that the code matrix has sufficient rank topermit the destination node 2105 to decode the received data. The sourcenode 2100 transmits the codes along with the encoded messages throughthe network via the intervening nodes 2102.1-2102.P.

FIG. 22B depicts an aspect of the disclosure wherein the interveningnodes 2102.1-2102.P provide a plurality P of received messages r₁, r₂, .. . , r_(P) on the plurality P of network paths 2103.1, 2103.2, . . . ,2103.P, respectively to the destination node 2105. In one aspect, eachof the received messages r₁, r₂, . . . , r_(P) comprises a unique linearcombination of P information messages (or symbols) x₁, x₂, . . . ,x_(P). For example, a p^(th) received message r_(p) may comprise avector of coefficients [β_(p,1), β_(p,2), . . . , β_(p,P)] that is a rowor column of a code matrix having rank P. In one aspect disclosed in the'163 application, the code matrix (e.g., channel-specific coding)comprises space-time or space frequency codes (e.g., pre-coding), suchas derived from channel measurements. The characteristic randomnessterrestrial wireless transmission paths (e.g., paths 2101.1-2101.Pand/or paths 2103.1-2103.P) can provide a code matrix of random valueswith rank P if the transmission paths (2101.1-2101.P and/or paths2103.1-2103.P) are sufficiently uncorrelated.

In one aspect of the disclosure, the destination node 2105 selects theintervening nodes 2102.1-2102.P to build up the rank of the receivedcoding matrix. For example, the destination node 2105 can select asufficient number of the intervening nodes 2102.1-2102.P to ensure thatthe code matrix has sufficient rank to permit the destination node 2105to decode the received data.

In some aspects of the disclosure, the intervening nodes 2102.1-2102.Pfunction as a cooperative-MIMO antenna array, which enables thedestination node 2105 to receive a sufficient number of linearlyindependent combinations of transmitted signals to permit demultiplexingof the received signals. In one aspect, signals received by each of theintervening nodes 2102.1-2102.P comprises a linear combination oftransmitted data signals, and the linear combinations and correspondingcode vectors received by the nodes 2102.1-2102.P are communicativelycoupled to the destination node 2105 via a fronthaul network comprisingthe paths 2103.1-2103.P. In another aspect of the disclosure, thedestination node 2105 comprises an antenna array (e.g., antenna system2115), and the transmission paths 2103.1-2103.P comprise the radioaccess network. The nodes 2102.1-2102.P transmit the codes along withthe encoded messages to the destination node 2105. In this aspect, thenodes 2102.1-2102.P and/or the transmission paths 2103.1-2103.P canprovide additional coding to the signals received at the destinationnode 2105. In some aspects, the code matrix may be determined by thedestination node 2105 by deriving channel measurements from training(e.g., pilot) signals in the received signals. In other aspects, controlsignals (such as known training signals) can be encoded such that areceiver, upon correcting for channel distortions, can determine thecode(s).

FIG. 23A is a flow diagram that illustrates aspects of the disclosurepertaining to cooperative subspace multiplexing. In one aspect, aplurality of cooperating nodes is selected to build the dimension of asubspace spanned by coded transmissions 2301. The plurality ofcooperating nodes may comprise a source node. In some aspects, thesource node communicates with cooperating transmitter nodes via afronthaul network.

Linear codes are generated 2302, for example, from channel estimates ofa scattering-rich propagation environment. The natural randomness ofterrestrial multipath channels can provide statistically random codes.In some aspects, linear coding is provided to transmissions viapre-coding based on channel measurements. In some aspects, linear codingmay be provided to transmissions by multipath in the propagationenvironment. In such aspects, linear codes corresponding to differenttransmission channels will be algebraically unique if the channels fromwhich the codes are derived are uncorrelated. This occurs when there issufficient scattering. Thus, employing multipath scattering for encodingtransmissions can be achieved by ensuring that transmitting antennas aresufficiently spatially separated to ensure uncorrelated subspacechannels.

In some aspects of the invention, linear codes are generated 2302 andthen the cooperating transmit nodes are selected 2301 to at least matchthe dimension of the set of linear codes (e.g., the rank of a resultingcode matrix). In other aspects, the linear codes are generated 2302 tomatch the dimension of the subspace enabled by a pre-selected set ofcooperating transmit nodes.

The cooperating transmit nodes transmit the coded messages and codematrix 2303. In one aspect, the code vectors are transmitted along withthe data payload. In some aspects, the code vectors may be included incontrol signals. For example, the code matrix may be conveyed byencoding known values, such as training signals. In some aspects, thenatural randomness of the channel encodes transmitted messages andtraining signals. Thus, transmitting the coded messages and code matrix2303 can comprise transmitting signals from cooperating transmit nodesthat are sufficiently spatially separated to provide uncorrelatedtransmission channels.

FIG. 23B is a flow diagram that illustrates aspects of the disclosurepertaining to cooperative subspace demultiplexing. In one aspect, aplurality of cooperating nodes is selected to build the dimension of asubspace spanned by received coded messages 2311. The plurality ofcooperating nodes may comprise a destination node.

A matrix of linear codes is determined from the received signals 2312.For example, cooperating receiver nodes can communicatively couple theirreceived messages to the destination node (or some other node(s)configured to perform MIMO subspace demultiplexing) via a fronthaulnetwork. In some aspects, the code matrix accompanies the receivedmessages in the data payload and/or as separate control information. Insome aspects, the code matrix is determined from measurements of knowntraining signals in the received messages.

In one aspect of the disclosure, determining the code matrix 2312 canindicate a required dimension that permits decoding. Thus, selectingcooperating nodes 2311 may be performed following step 2312, such as toensure that a sufficient number of linearly independent combinations ofthe original messages are collected to enable decoding. Once thedestination node (or at least one other node configured to perform MIMOsubspace demultiplexing) receives a sufficient number of linearlyindependent combinations, the received messages are decoded 2313.

FIG. 24A is a block diagram depicting a transceiver and transceivermethod configured to perform routing in accordance with some aspects ofthe invention. In one aspect, each block comprises a step or set ofsteps, which can be performed by one or more circuits or machinecomponents, such as a specialized computing device programmed withinstructions to perform specific functions. In one aspect, each blockcomprises a circuit or a portion of a circuit in a transceiverapparatus. In another aspect, each block comprises a set of instructionsthat programs a specialized computing device to perform one or moresteps disclosed herein. In another aspect, each block and/or a pluralityof the blocks comprises at least one specialized computing deviceprogrammed with instructions to perform specific functions.

Transmitted signals are received by a receiver system 2401 that outputsa baseband signal. In a wireless network, the receiver system 2401performs RF and, optionally, baseband processes typically performed toconvert an RF signal to a baseband or intermediate frequency signal. Forexample, the receiver system 2401 may perform channel selection,filtering, amplification, frequency conversion, and A/D conversion.

In one aspect, each transmitted signal comprises a coded data payloadand a preamble (or header) that comprises the code. The codes maycomprise channel-specific coding. A decoder 2402 can be configured todecode the baseband signal relative to one or more codes in the header.A signal processor 2403 may process the decoded signals prior toproducing an output data stream. Signal processing may include one ormore signal-processing operations, including, but not limited to,quantization, channel decoding, multiple access decoding,demultiplexing, formatting, demodulation, channel estimation, channelcompensation, synchronization, filtering, error detection, errorcorrection, signal-quality analysis, multi-user detection, phase-jittercompensation, frequency-offset correction, time-offset correction, etc.

A control system 2404 is configured to select, adapt, or otherwisecontrol the operation of one or more transceiver components. Forexample, channel estimates and/or signal-quality analysis performed bythe signal processor 2403 may be processed in the control system 2404,such as to adapt decoding performed by the decoder 2402. The controlsystem 2404 may provide power control to a transmission system (e.g.,transmission system 2406) and/or otherwise provide network control.Similarly, coding may be adapted by the control system 2404.

A pre-coder 2405 is configured to process input data bits to produce acoded signal that is coupled to the transmission system 2406. Thetransmission system 2406 performs signal-processing operations typicallyperformed to prepare a baseband signal for transmission into acommunication channel. In a wireless network, the transmission system2406 may perform one or more processes, including, but not limited to,D/A conversion, modulation, filtering, amplification, frequencyconversion, beam forming, etc.

Signals from the receiver system 2401 can also be coupled through arouting system 2410. In one aspect, signals from the receiver system2401 are coupled to a decoder 2412, which may include a bank ofdecoders. In one aspect of the disclosure, the decoder 2412 decodesreceived signals that are to be retransmitted. The decoded signals areprocessed in a signal processor 2413, which may perform similarsignal-processing operations as signal processor 2403. Furthermore, thesignal processor 2413 may perform pre-processing operations prior tocoding in a pre-coder 2415. The pre-coder 2415 may include a bank ofpre-coders. A control system 2414 may be configured to select, adapt, orotherwise control the operation of one or more of the transceivercomponents 2412, 2413, and 2415.

In one aspect, the control system 2414 and the coder 2415 may providechannel-compensation and/or beam-forming weights to the coded symbols.Such weights may be regarded as part of the routing process (e.g., thepre-coding). In some aspects, since routing decodes some signals thatare not intended for the transceiver, the router components 2412, 2413,2414, and 2415 can be isolated from the rest of the transceiver by afire wall 2410.

In one aspect, the set of router components 2412, 2413, 2414, and 2415receives signals to be routed, decodes the signals 2412, cleans up thedecoded signals 2413, and re-encodes the cleaned-up signals 2415 forretransmission 2406. Additional pre-coded signals (e.g., from thepre-coder 2405) can be combined with the pre-coded signals from thepre-coder 2415 prior to retransmission 2406. As indicated by thejunction that joins the pre-coder 2405 and the pre-coder 2415 prior tothe transmitter 2406, pre-coded signals to be routed may be summed withpre-coded “Data Input,” which produces linear combinations of pre-codedsignals.

As disclosed in the '850 and '163 applications, in some aspects, thedecoder 2412 does not decode some or all of the input coded signals.Rather, the decoder 2412 maps the input coded signals to different codespaces. For example, when basic linear CI codes are employed, the codecoefficients resemble Fourier Transform coefficients which aredistributed uniformly on the unit circle in the complex plane. Oneadvantage to using basic linear CI codes is that such codes areorthogonal, and some implementation do not require transmitting thedecode vector(s) with the coded transmission. Orthogonal codes comprisedifferent integer numbers of “rotations” on the unit circle in thecomplex plane. For non-zero rotations, a vector sum of the codecoefficients produces a zero result. For a zero rotation, all the codevalues are mapped to the same point on the unit circle, so the codevalues sum coherently. Decoding 2412 can map an input code having afirst number of rotations to an output code having a second number ofrotations. If the second number of rotations is zero, then summing theresult yields a solution for a code space in the set of linearlyindependent coded data values whose coefficients are basic linear CIcode values. Thus decoding 2412 can solve for one or more unknowns(i.e., information signals) in the set of linear combinations and/or mapat least one code space to at least another code space.

In one aspect of the disclosure, communication signals comprise codedsets of low-bandwidth subchannels. Thus, interference resulting frommultipath and effective multipath resulting from retransmissions throughthe network can be reduced to flat fades. Sub-carrier bandwidths may beadapted to the multipath channel in one or more parts of the network.Coding may be adapted with respect to one or more parameters, includinggeographical distributions of subscriber units and access points,channel conditions, link priority, security, subscriber services, numberof subscribers, etc.

In some aspects of the disclosure, each network node has access to thecommunity's transmissions. The system can allow each node to dynamicallyselect for reception only those transmissions that are relevant to thatnode. Individual transceivers may be equipped with adaptable orprogrammable decoders designed to select and decode one or moretransmissions. The transceivers may be provided with a bank of decodersto decode and process multiple received signals simultaneously.

FIG. 24B is a block diagram of a transceiver configured to performrouting in accordance with aspects of the invention. It should beappreciated that FIG. 24B, as well as the other block diagrams of thedisclosure, can indicate both apparatus and method implementations. Forexample, the blocks can indicate circuits, devices, systems, or otherphysical components of an apparatus or system. In some aspects, theblocks indicate functional components. The grouping of the functionalcomponents can take different physical forms. In some aspects, more thanone block may be embodied by one particular physical component. In someaspects, a plurality of physical components can be employed as one ofthe blocks. In some aspects disclosed in the '850 and '163 applications,at least some of the disclosed signal processing operations can beperformed by a computer processor and a computer-readable memorycomprising processing instructions that instruct the processor tophysically change input signals.

In the transceiver depicted in FIG. 24B, signals from the receiver 2401are coupled through a routing system 2420 and then retransmitted by thetransmitter 2406. The routing system 2420 can comprise a processor 2419configured to process received signals to be routed, and then outputtingprocessed signals to the transmitter 2406. The received signals to berouted may comprise baseband and/or intermediate-frequency (IF) signals.The processor 2419 can be configured to perform one or more baseband orIF processes, including, but not limited to, signal shaping, filtering,re-quantization, error detection, error correction, interferencemitigation, multi-user detection, amplification, up sampling, downsampling, frequency conversion, D/A conversion, AGC, symbol remapping,etc.

It should be appreciated that in some aspects, retransmitting (e.g.,relaying, routing, and/or repeating) the received signal can effectivelyincrease the rank of the channel matrix H from the perspective of thedestination receiver(s), particularly if propagation channel is ascattering-rich environment. The rank of H is the sum of non-zerosingular values λ_(i) in which each λ_(i) corresponds to an eigenmode ofthe channel (i.e., an eigen-channel, or subspace channel). Each non-zeroeigenmode can support a data stream, thus the MIMO channel can support kspatial sub-space channels, where k is the number of non-zeroeigenvalues λ_(i).

In accordance with some aspects of the disclosure, base-stationresponsibilities are assigned to (or assumed by) individual UEs. Forexample, base-station operations can be coordinated with simultaneouscoded transmissions of a traffic channel and a control channel. Codesmay include CI codes, CI-based coding, channel-specific coding, or anycombination thereof. A time division duplexing method may be employedfor transmit and receive operations to implement the necessary controlfunctions for operation without a base station. At least one of the UEscan be assigned to be a network control station. By using time divisionduplexing for transmit and receive operations, the same frequencyband(s) can be used for uplink and downlink, which can simplify channelestimation and MIMO processing.

A UE acting as a network control station can maintain power control andtime synchronization normally performed by a base station. For example,power control can be maintained within predetermined time intervals by afeedback control loop using proportional integration and differentiationto smooth control such that power oscillations are maintained withindesired limits. The network control functions may automatically betransferred if the connection with the transceiver is terminated orthere is a predetermined degree of signal-quality degradation. Thenetwork control station can have channel control capabilities to assuretransmission security. For example, the network control station mayassign codes to other UEs to change the security or priority ofindividual communication links.

FIG. 25A is a block diagram illustrating a network configuration thatemploys channel reuse between a plurality of networks. A signal 2500having channel allocation C₁ in a first network is received by atransceiver 2510 (with antenna system 2520). For example, the firstnetwork may comprise a WWAN, or “macro-cell.” The channel C₁ is reusedfor communication in a second network (e.g., a micro-cell network) 2550comprising transceivers 2510-2513. For example, transmissions 2501-2503employ the channel allocation C₁. As disclosed in the '163 application,the transmissions 2501-2503 can comprise array-processing pre-coding,which can permit reuse of the channel allocation C₁ by the secondnetwork via interference mitigation.

In one aspect of the disclosure, antenna systems 2520, 2521, 2522, and2523 may comprise multiple antennas, and each transceiver 2510, 2511,2512, and 2513 may be configured to perform array processing with itsown antenna system. In another aspect of the invention, the transceivers2510, 2511, 2512, and 2513 can be configured to perform cooperativearray processing, wherein array processing (such as subspace processing)operations are jointly processed by multiple ones of the transceivers2510, 2511, 2512, and 2513. Combinations of local array processing(i.e., array processing on individual transceivers) and cooperativearray processing (e.g., Cooperative MIMO) may be performed.

FIG. 25B is a block diagram illustrating a network configuration thatemploys cooperative array processing and reuses channel C₁ allocated toa first link 2500. In one aspect, a plurality of the transceivers (2511,2512, and 2513) employs channel C₁ to communicate with transceiver 2520.For example, the transceivers 2511, 2512, and 2513 transmit signals2504, 2505, and 2506, respectively, to transceiver 2510. Pre-codingoperations on the transmitted signals 2504, 2505, and 2506 can providefor beam forming (or equivalent array processing) operations. Variouscombining operations may be provided to produce any combination ofinterference rejection, diversity enhancement, and sub-space processing(i.e., capacity enhancement). The afore-mentioned operations can permita micro-cell network (e.g., network 2550) to employ the same macro-cellchannels (e.g., channel C₁) without interfering with the macro-cellnetwork.

Methods described with respect to FIGS. 25A and 25B and the relateddisclosures in the '163 application, the transceivers 2510, 2511, 2512,and 2513 can be implemented, by way of example and without limitation,with apparatus embodiments depicted in and described with respect toFIGS. 24A and/or 24B.

FIG. 26 is a block diagram depicting systems and methods according tosome aspects of the disclosure. In one aspect, a cooperative-MIMOnetwork 2660 comprises multiple groups of separate geographicallydistributed transceivers, wherein at least a first group 2651 employscooperative subspace processing (e.g., cooperative-MIMO) to communicatewith at least a second group 2652, such as disclosed in the '107 and'163 applications. In one aspect of the disclosure, the firsttransceiver group 2651 comprising transceivers 2610-2613 is configuredto communicate subspace signals 2601-2603 employing a common channel C₁to the second transceiver group 2652, which comprises transceivers2614-2616. Since the transceivers 2610-2616 can be configured to operatein multiple networks (e.g., macro-cell and micro-cell networks), in oneaspect, network 2660 can be a micro-cell network configured to reusechannel C₁, which is used for communication in the macro-cell.

The subspace signals 2601-2603 comprise a plurality of spatialsubchannels that occupy a common frequency spectrum, time interval, andcode space denoted by the common channel C₁, wherein subspace processingprovides for non-interfering parallel subchannels. As disclosed herein,subspace processing can comprise any combination of transmitter-side andreceiver side subspace processing. For example, subspace processing cancomprise pre-coding (i.e., spatial multiplexing). In some aspects,subspace processing comprises subspace decoding (i.e., spatialdemultiplexing).

The transceivers 2610-2616 each comprises an antenna system (e.g.,antenna systems 2620-2626, respectively), that includes one or moreantennas. Thus, in some aspects, more than one antenna per transceivercan be available for cooperative-MIMO processing. In some aspects, oneor more of the transceivers 2610-2616 can perform local antenna arrayprocessing (e.g., diversity combining and/or spatial multiplexing) inaddition to participating in cooperative-subspace processing. As usedherein, “spatial multiplexing” can denote the general practice ofsubspace processing, which can comprise pre-coding (also referred to assubspace coding or spatial multiplexing) and/or decoding (also referredto as subspace decoding or spatial demultiplexing). In some cases,“spatial multiplexing” specifically denotes subspace processing on thetransmitter side of a communication link (which is distinguished fromspatial demultiplexing performed on the receiver side of the link), and,thus, comprises subspace coding (also referred to as pre-coding). Theintended scope of the terminology used in the disclosure is indicated bythe context in which it is used.

With reference to FIGS. 25A, 25B, and 26, and related disclosures in the'163 application, FIG. 27 is a flow diagram that depicts methodsaccording to some aspects of the invention. In one aspect, a clienttransceiver (i.e., a client node) receives a channel allocation (e.g.,channel C₁) for communicating in a first communication link 2701. Forexample, the client transceiver may receive a signal in channel C₁.Alternatively, the client transceiver may be allocated channel C₁ fortransmitting signals. The channel allocation C₁ typically comprises aspecified frequency band, time interval, and code space. When nomultiple access codes are employed, the code space is simply a vector ofones (e.g., [1, 1, 1, . . . , 1]). By way of example, the channel C₁ maybe allocated for communication between the client transceiver and atleast one other transceiver in the first network, the channel C₁ beingallocated so as not to interfere with other communication links in thefirst network.

A “client transceiver,” as used herein, indicates a transceiver that isserved by a first network via the first communication link. In someaspects of the disclosure, the client transceiver may perform additionalnetwork functions, and as such, may function as any of various networkdevices, such as a router, a relay, a repeater, or a gateway.

A transceiver group comprising multiple transceivers, including theclient transceiver, is selected to communicate in a second communicationlink 2702. In one aspect, selecting 2702 comprises provisioning aplurality of the transceivers to cooperatively transmit signals in thesecond link. In another aspect, selecting 2702 comprises provisioning aplurality of the transceivers to cooperatively receive signals in thesecond link. Pluralities of both transmitting and receiving transceiversmay be selected, such as depicted in FIG. 26.

In some aspects, the client transceiver functions as a router or relay,such as to forward communications it receives via the first link to adestination node or another intermediate node via at least a secondlink. The client may select 2702 the transceivers to which it forwardscommunications. In one aspect, communications forwarded by the clienttransceiver to a plurality of cooperating transceivers constitute thesecond link. In another aspect, transmissions from cooperatingtransceivers (which may or may not include the client transceiver)comprise the second link. In one aspect, the first link is part of afirst network and the second link is part of a second network.

The channel C₁ is reused for communicating in the second link 2703.Specifically, the second link simultaneously employs the same frequencyband and code space as in the first link. Thus, some aspects of theinvention are configured to mitigate co-channel interference betweensignals in the first and second links. Some aspects employ cooperativesubspace processing 2704 between at least two transceivers communicatingin the second link to mitigate interference between signals in the firstand second links. For example, spatial multiplexing (i.e., pre-coding)performed by a plurality of cooperating transmitters can canceltransmissions in the second link that would otherwise interfere with thereception of transmissions in the first link. Spatial de-multiplexing(i.e., subspace decoding) performed by cooperating transmitters canseparate interfering first-link and second-link signals, such as topermit reception of either or both first-link and second-link signals bytransceivers operating in the second link.

By way of example, if the first link channel C₁ is a downlink channel,then cooperative subspace multiplexing and/or demultiplexing canseparate received second-link signals from received first-link signalswithin the transceiver group. By way of example, if the first-linkchannel C₁ is an uplink channel, then cooperative subspace multiplexing(e.g., pre-coding) can cancel co-channel interference due to second-linksignals received by receivers communicating in the first link. Also,cooperative subspace multiplexing and/or demultiplexing can separatereceived second-link signals from received first-link signals within thetransceiver group.

As will be appreciated to those skilled in the art, disclosures of the'850 and '163 applications can be employed in various types ofcommunication networks, including LTE networks, which comprise a flatnetwork architecture as opposed to hierarchical architectures of othercellular standards.

Thus, in accordance with some aspects of the disclosure, the UEsdisclosed herein comprise LTE UEs. By way of example, a UE may comprisean RF transceiver for fixed and/or mobile clients receiving data streamsover a downlink channel(s) in the radio access network and transmittingdata via the uplink channel(s) in the radio access network.

A base transceiver station may comprise an eNodeB, which may handleradio resource management, user mobility, and scheduling. The basetransceiver stations interface the fronthaul network with the radioaccess network. A base transceiver station of one aspect of thedisclosure is an access point comprising an RF front-end configured toconvert baseband signals to RF and RF signals to baseband. The basetransceiver station may comprise a Digital-to-Analog Converter(DAC)/Analog-to-Digital Converter (ADC). In some aspects, the basetransceiver station is a simple RF transceiver equipped with poweramplifier/antenna(s), and RF signals are communicatively coupled betweenthe base transceiver station and the central processor via the fronthaulnetwork, which can include RF-over-fiber technology, such as describedin related patents and applications that are incorporated by reference.

A controller employed in an LTE network may comprise a base transceiverstation configured to perform certain specialized functions, such astransmitting training signals, receiving/transmitting controlinformation from/to the UEs, receiving channel state information (CSI)or channel quality information from the UEs, etc. Coordinated multipointsystems disclosed herein may comprise multiple controllers. In an LTEnetwork, the controller may comprise a mobility management entity.

A fronthaul network configured in an LTE system may comprise acombination of S1 and X2 interfaces. By way of example, but withoutlimitation, the fronthaul may comprise S1-MME links between the mobilitymanagement entity and eNodeBs, S1-U links between the serving gatewayand eNodeBs, and X2 links between multiple eNodeBs. In some aspects, thefronthaul network comprises the S1 interface. In other aspects, thefronthaul network comprises the X2 interface.

The LTE network typically comprises a gateway, which comprises a servinggateway (S-GW) that terminates the E-UTRAN interface, and a PDN gateway(P-GW), which interfaces with external networks. In accordance withaspects of the disclosure, the central processor can be implemented bythe gateway, such as the S-GW component. In other aspects, one or moreof the eNodeBs can be configured to operate as the central processor.

While aspects of the disclosure describe Cooperative-MIMO processing inwhich high channel selectivity (wherein selectivity refers tostatistical variations of spatial gains of propagating signals) isachieved via rich multipath environments and/or geographicallydistributed transmitters (and/or receivers), alternative aspects mayemploy other diversity parameters (such as signal polarization) and/orvarious techniques (e.g., coherence multiplexing, frequency diversityinterferometry, etc.), such as described in Applicant's patents andother applications, to achieve channel selectivity. By way of example,in U.S. Pat. No. 6,331,837, which is hereby incorporated by reference inits entirety, Applicant discloses that different antenna beam patternscan provide for different spatial gains, thereby providing theselectivity necessary to achieve spatial multiplexing and/orde-multiplexing. Specifically, subspace processing can be achieved inthe beamspace domain of a transmitting and/or receiving array, thustransferring the MIMO operation from the antenna elements to thebeamspace. Data streams are mapped onto specific transmitted beampatterns, and beamspace multiplexed data streams are sentsimultaneously. Similarly, specific radiation patterns are used toreceive transmissions. Since beamspace multiplexing exploits aerialdegrees of freedom, such techniques can be advantageous for arrays withclosely spaced elements. In some aspects of the disclosure, one or moreantenna elements in an array are parasitic elements.

One aspect of the '837 patent discloses outputs from multiplebeamforming processes being input to a spatial de-multiplexing process.In the case wherein the number of active receiving antennas is less thanthe number of transmitting antennas, if the beamforming processesproduce a number of linearly independent combinations of receivedtransmissions at least equal to the number of transmit sources, thenthere is sufficient rank in the resulting channel matrix to separate thereceived signals. In one sense, the beamforming process can beimplemented as a multiple-access coding process that maps M logicalchannels onto N physical subspace channels, where M>N. Although thetotal theoretical capacity of the channel (such as expressed by thecorresponding Shannon-Hartley theorem for the corresponding MIMOimplementation employed) does not increase, the capacity is partitionedacross more subchannels. In one aspect, the M subchannels each have alower SNR (and thus smaller capacity) than the corresponding Nsubchannels. This could be a result of more correlation between theelements of the channel matrix as its dimension increases. Thereciprocal of any such process can be applied to spatial multiplexing.Various techniques, including coherence multiplexing, polarizationsubspace multiplexing, and frequency diversity interferometry aredescribed, and these and the other disclosed techniques can be employedwithin the spatial multiplexing and de-multiplexing methods and systemsdisclosed herein.

The various blocks shown in the figures may be viewed as method steps,and/or as operations that result from operation of computer programcode, and/or as a plurality of coupled logic circuit elementsconstructed to carry out the associated function(s).

In general, the various exemplary aspects may be implemented in hardwareor special purpose circuits, software, logic or any combination thereof.For example, some aspects may be implemented in hardware, while otheraspects may be implemented in firmware or software which may be executedby a controller, microprocessor or other computing device, although theinvention is not limited thereto. While various aspects of the exemplaryembodiments of this invention may be illustrated and described as blockdiagrams, flow charts, or using some other pictorial representation, itis well understood that these blocks, apparatus, systems, techniques ormethods described herein may be implemented in, as non-limitingexamples, hardware, software, firmware, special purpose circuits orlogic, general purpose hardware or controller or other computingdevices, or some combination thereof.

It should thus be appreciated that at least some aspects of theexemplary aspects of the invention may be practiced in variouscomponents such as integrated circuit chips and modules, and that theexemplary aspects of this invention may be realized in an apparatus thatis embodied as an integrated circuit. The integrated circuit, orcircuits, may comprise circuitry (as well as possibly firmware) forembodying at least one or more of a data processor or data processors, adigital signal processor or processors, baseband circuitry and radiofrequency circuitry that are configurable so as to operate in accordancewith the exemplary aspects of this invention.

Various modifications and adaptations to the foregoing exemplary aspectsof this invention may become apparent to those skilled in the relevantarts in view of the foregoing description, when read in conjunction withthe accompanying drawings. However, any and all modifications will stillfall within the scope of the non-limiting and exemplary aspects of thisinvention.

The invention claimed is:
 1. A multi-user multiple antenna system,comprising: a central processor; and a plurality of geographicallydistributed access points communicatively coupled to the centralprocessor via a network and configured to serve a plurality of clientdevices; wherein the central processor, the plurality of geographicallydistributed access points, or the plurality of client devices computeschannel estimates of wireless channels between the geographicallydistributed access points and the client devices; and wherein thecentral processor computes access-point weights from the channelestimates to synthesize an antenna array from the plurality ofgeographically distributed access points that implements spatialmultiplexing.
 2. The system of claim 1, wherein the access-point weightsconfigure transmitted signals from the plurality of geographicallydistributed access points to constructively combine at one or moreclient devices and produce nulls at one or more other client devices. 3.The system of claim 1, wherein the access-point weights are employed forcombining signals received by the plurality of geographicallydistributed access points.
 4. The system of claim 1, wherein the centralprocessor is configured to perform at least one of modulation, coding,synchronization, power control, and multiple-access control of signalstransmitted by the plurality of geographically distributed accesspoints.
 5. The system of claim 1, wherein each of the plurality ofgeographically distributed access points employs a local or globaltiming reference for transmitting and receiving signals.
 6. The systemof claim 1, wherein each client device is served by multiple ones of theplurality of geographically distributed access points, the multiple onesbeing selected to serve the each client device based on measured signalpower of transmissions from the each client device received by theplurality of geographically distributed access points.
 7. The system ofclaim 1, wherein the channel estimates comprise at least one ofdelay-profile and flat-fading characterizations.
 8. The system of claim1, wherein each of the plurality of geographically distributed accesspoints comprises one of a single antenna system or a multi-antennasystem.
 9. The system of claim 1, wherein the access-point weights arecomputed from the reciprocal of a channel matrix.
 10. The system ofclaim 1, wherein each of the plurality of geographically distributedaccess points comprises at least one of a client device assigned tofunction as an access point, a base station in a mobile radio network, arouter, or a relay.
 11. The system of claim 1, wherein the networkcomprises at least one of a wireless network, an optical fiber network,and a wireline network.
 12. A method implemented in a multi-usermultiple antenna system configured to serve a plurality of clientdevices, comprising: communicatively coupling a central processor to aplurality of geographically distributed access points via a network;computing, by the central processor, the plurality of geographicallydistributed access points, or the plurality of client devices, channelestimates of wireless channels between the geographically distributedaccess points and the client devices; and computing access-point weightsfrom the channel estimates to synthesize an antenna array from theplurality of geographically distributed access points for implementingspatial multiplexing.
 13. The method of claim 12, further comprisingperforming time-division duplexing for transmitting and receivingsignals.
 14. The method of claim 12, further comprising transmitting orreceiving pilot signals or training signals by the plurality ofgeographically distributed access points.
 15. The method of claim 12,wherein spatial multiplexing comprises transmitting weighted signals bythe plurality of geographically distributed access points, such thatweighted transmissions constructively combine at one or more clientdevices and produce nulls at one or more other client devices.
 16. Themethod of claim 12, wherein spatial multiplexing comprises employing theaccess-point weights for combining signals received by the plurality ofgeographically distributed access points.
 17. The method of claim 12,further comprising performing at least one of modulation, coding,synchronization, power control, and multiple-access control of signalstransmitted by the plurality of geographically distributed accesspoints.
 18. The method of claim 12, further comprising employing a localor global timing reference for transmitting and receiving signals. 19.The method of claim 12, further comprising: measuring signal powers ofclient device transmissions received by the plurality of geographicallydistributed access points; and selecting multiple ones of the pluralityof geographically distributed access points to serve each client devicebased on the signal powers.
 20. The method of claim 12, whereincomputing the channel estimates comprises computing at least one ofdelay and flat fading.
 21. The method of claim 12, further comprisingperforming local array processing of signals transmitted or received ateach of the plurality of geographically distributed access points. 22.The method of claim 12, wherein computing the access-point weightscomprises computing the reciprocal of a channel matrix.
 23. The methodof claim 12, wherein each of the plurality of geographically distributedaccess points comprises at least one of a client device assigned tofunction as an access point, a base station in a mobile radio network, arouter, or a relay.
 24. The method of claim 12, wherein the access-pointweights comprises subcarrier weights applied to subcarriers of anOrthogonal Frequency Division Multiplexing (OFDM) signal.